Electron beam therapy planning and custom electron bolus design were identified as areas in which improvements in equipment and techniques could lead to significant improvements in treatment delivery and patient outcomes. The electron pencil beam algorithms used in conventional Treatment Planning Systems do not accurately model the dose distribution in irregularly shaped objects, near oblique surfaces or in inhomogeneous media. For this reason, at Christchurch Oncology Centre the TPS is not relied on for planning electron beam treatments. This project is an initial study of ways to improve the design of custom electron bolus, the planning of electron beam therapy, and other radiation therapy simulation tasks, by developing a system for the accurate assessment of dose distributions under irregular contours in clinically relevant situations. A shaped water phantom system and a diode array have been developed and tested. The design and construction of this water phantom dosimetry system are described, and its capabilities and limitations discussed. An EGS/BEAM Monte Carlo simulation system has been installed, and models of the Christchurch Oncology Centre linacs in 6MeV and 9MeV electron beam modes have been built and commissioned. A test was run comparing the EGS/BEAM Monte Carlo system and the CMS Xio conventional treatment planning system with the experimental measurement technique using the water phantom and the diode array. This test was successful as a proof of the concept of the experimental technique. At the conclusion of this project, the main limitation of the diode array system was the lack of data processing software. The array produces a large volume of raw data, but not enough processed data was produced during this project to match the spatial resolution of the computer models. An automated data processing system will be needed for clinical use of the array. It has been confirmed that Monte Carlo and pencil-beam algorithms predict significantly different dose distributions for an irregularly shaped object irradiated with megavoltage electron beams. The results from the diode array were consistent with the theoretical models. This project was an initial investigation. At the time of writing, the diode array and the water phantom systems were still at an early stage of development. The work reported here was performed to build, test and commission the equipment. Additional work will be needed to produce an instrument for clinical use. Research into electron beam therapy could be continued, or the equipment used to expand research into new areas.

In 1996, a concept was proposed by the UK Ministry of Defence with the intention of making the field of reliability more useful to the end user, particularly within the field of military aerospace. This idea was the Maintenance Free Operating Period (MFOP), a duration of time in which the overall system can complete all of its required missions without the need to undergo emergency repairs or maintenance, with a defined probability of success. The system can encounter component or subsystem failures, but these must be carried with no effect to the overall mission, until such time as repair takes place. It is thought that advanced technologies such as redundant systems, prognostics and diagnostics will play a major role in the successful use of MFOP in practical applications. Many types of system operate missions that are made up of several sequential phases. For a mission to be successful, the system must satisfactorily complete each of the objectives in each of the phases. If the system fails or cannot complete its goals in any one phase, the mission has failed. Each phase will require the system to use different items, and so the failure logic changes from phase to phase. Mission unreliability is defined as the probability that the system fails to function successfully during at least one phase of the mission. An important problem is the efficient calculation of the value of mission unreliability. This thesis investigates the creation of a modelling method to consider as many features of systems undergoing both MFOPs and phased missions as possible. This uses Petri nets, a type of digraph allowing storage and transit of tokens which represent system states. A simple model is presented, following which, a more complex model is developed and explained, encompassing those ideas which are believed to be important in delivering a long MFOP with a high degree of confidence. A demonstration of the process by which the modelling method could be used to improve the reliability performance of a large system is then shown. The complex model is employed in the form of a Monte-Carlo simulation program, which is applied to a life-size system such as may be encountered in the real world. Improvements are suggested and results from their implementation analysed.

Growth mechanism of electroplated copper columns has been systematically studied by simulations and characterizations. A two-dimensional cross-sectional kinetic Monte Carlo (2DCS-KMC) model has been developed to simulate the electrodeposition of single crystal copper. The evolution of the microstructure has been visualized. The cluster density, average cluster size, variance of the cluster size and average aspect ratio were obtained from the simulations. The growth history of the deposition from the first atom to an equivalent of 100 monolayers was reconstructed. Following the single-lattice 2DCS-KMC model for a single crystal, a two-dimensional cross-sectional poly-lattice kinetic Monte Carlo (2DCSP-KMC) model has been developed for simulation of the electrodeposition of polycrystalline copper on both a copper and a gold substrate. With this model, the early-stage nucleation and the grain growth after impingement of nuclei can be simulated; as such the entire growth history is reconstructed in terms of the evolution of microstructure, grain statistics and grain boundary misorientation. The model is capable of capturing some key aspects of nucleation and growth mechanisms including the nucleation type (e.g. homogeneous or heterogeneous), texture development, the growth of grains and higher energetic state of grain boundaries. The model has also proven capable of capturing the effects of deposition parameters including applied electrode potential, concentration of cupric ions and temperature. Their effects are largely dependent on the substrates. The early-stage electrocrystallization of Cu on polycrystalline Au has been studied by ex-situ AFM observations. The evolution of surface morphology of the electrodeposited copper on a sputtered Au seed layer from 16ms to 1000s was observed and their formation mechanism discussed. The heterogeneous nucleation phenomenon, the competitive growth both longitudinally and laterally, and the dominant growth of some nuclei were experimentally observed, which are also visualized by the relevant KMC simulation results at a smaller size scale and a shorter time scale. A heuristic model is therefore proposed to describe the mechanism of the early-stage electrocrystallization of Cu on a polycrystalline Au seed layer. Electroplated copper columns plated for different times have been characterized in terms of the evolution of their external morphology, cross-sectional microstructure and crystal structure. The microstructure of electroplated copper columns is characteristic of bi-modal or tri-modal grain size distribution. The results indicate that recrystallization has occurred during or after the plating, top-down and laterally. Slight changes of the crystal structure were observed by in-situ XRD and it was found that the changes of the (111) and (200) planes occurred at different stages of self-annealing. Finally, the results indicate the presence of organic additives is not essential for self-annealing of a copper column to occur.

The growth of the financial risk management industry has been motivated by the increased volatility of financial markets combined with the rapid innovation of derivatives. Since the 1970s, several financial crises have occurred globally with devastating consequences for financial and non-financial institutions and for the real economy. The most recent US subprime crisis led to enormous losses for financial and non-financial institutions and to a recession in many countries including the US and UK. A common lesson from these crises is that advanced financial risk management systems are required. Financial risk management is a continuous process of identifying, modeling, forecasting and monitoring risk exposures arising from financial investments. The Value at Risk (VaR) methodology has served as one of the most important tools used in this process. This quantitative tool, which was first invented by JPMorgan in its Risk-Metrics system in 1995, has undergone a considerable revolution and development during the last 15 years. It has now become one of the most prominent tools employed by financial institutions, regulators, asset managers and nonfinancial corporations for risk measurement. My PhD research undertakes a comprehensive and practical study of market risk modeling in modern finance using the VaR methodology. Two newly developed risk models are proposed in this research, which are derived by integrating volatility modeling and the quantile regression technique. Compared to the existing risk models, these two new models place more emphasis on dynamic risk adjustment. The empirical results on both real and simulated data shows that under certain circumstances, the risk prediction generated from these models is more accurate and efficient in capturing time varying risk evolution than traditional risk measures. Academically, the aim of this research is to make some improvements and extensions of the existing market risk modeling techniques. In practice, the purpose of this research is to support risk managers developing a dynamic market risk measurement system, which will function well for different market states and asset categories. The system can be used by financial institutions and non-financial institutions for either passive risk measurement or active risk control.

The aim of this doctoral research is to understand domain evolution processes in ferroelectrics using piezoresponse force microscopy (PFM) and Monte Carlo simulation. The results provide improved knowledge of domain evolution processes, and systematic experimental methods for research on domain evolution. There has been extensive previous research on domain evolution in ferroelectrics, but the research was mainly constrained to simple domain patterns. However, ferroelectric domains tend to form complex patterns that generate low-energy domain configurations. In this research, several methods such as statistical analysis of PFM data, ex situ/in situ PFM observation under electrical/mechanical loading and combining PFM with electron backscatter diffraction are employed to study domain evolution processes in complex domain patterns. The results show that domain switching almost always takes place by the evolution of pre-existing domain patterns, rather than direct flipping of polarization. Also the net effect of domain evolution processes follows a primary principle that positive work is done by external loads. But this principle is not always followed for microscopic switching processes. Multiple types of domain switching occur simultaneously, and occasionally an overwriting process involves unfavourable as well as favourable domain switching. Domain switching is significantly constrained by the pre-existing domain patterns. Meanwhile, angle-resolved PFM is developed for the systematic interpretation of PFM signal. Using lateral PFM images taken from multiple sample orientations, angle-resolved PFM maps are generated based on the angle of phase reversal in the PFM signal. The resulting maps reliably show complex domain patterns which may not appear in vertical and lateral PFM images. A model of domain evolution is developed using Monte Carlo simulation. Polarization switching by electric field and mechanical stress in the model is shown to take place via the motion of domain walls between pre-existing domains. Typical domain broadening processes are reproduced through this simulation.

Radio-Frequency (RF) lesioning, or RF ablation, is a method that uses high frequency currents for thermal coagulation of pathological tissue or signal pathways. The current is delivered from an electrode, which also contains a temperature sensor permitting control of the current at a desired target temperature. In the brain, RF lesioning can e.g. be used for treatment of severe chronic pain and movement disorders such as Parkinson’s disease. This thesis focuses on modelling and simulation with the aim of gaining better understanding and predictability of the lesioning process in the central brain.   The finite element method (FEM), together with experimental comparisons, was used to study the effects of electric and thermal conductivity, blood perfusion (Paper I), and cerebrospinal fluid (CSF) filled cysts (Paper II) on resulting lesion volume and shape in brain tissue. The influence of blood perfusion was modelled as an increase in thermal conductivity in non-coagulated tissue. This model gave smaller simulated lesions with increasing blood perfusion as heat was more efficiently conducted from the rim of the lesion. If the coagulation was not taken into consideration, the lesion became larger with increasing thermal conductivity instead, as the increase in conducted heat was compensated for through an increased power output in order to maintain the target temperature. Simulated lesions corresponded well to experimental in-vivo lesions. The electric conductivity in a homogeneous surrounding had little impact but this was not true for a heterogeneous surrounding. CSF has a much higher electric conductivity than brain tissue, which focused the current to the cyst if the electrode tip was in contact with both a cyst and brain tissue. Heating of CSF could also cause considerable convective flow and as a result a very efficient heat transfer. This affected both simulated and experimental lesion sizes and shapes. As a result both very large and very small lesions could be obtained depending on whether sufficient power was supplied or if the heating was mitigated over a large volume.   Clinical (Paper IV) and experimental (Paper III) measurements were used for investigation of changes in reflected light intensity from undamaged and coagulating brain tissue respectively. Monte Carlo (MC) simulations for light transport were made for comparison (Paper V). For the optical measurements, an RF electrode with adjacent optical fibres was used and this electrode was also modelled for the optical simulations. According to the MC simulations, coagulation should make grey matter lighter and white matter darker, while thalamic light grey should remain approximately the same. Experiments in ex-vivo porcine tissue gave an increase in reflected light intensity from grey matter at approximately 50 °C but the signal was very variable and the isotherm 60 °C gave better agreement between simulated and experimental lesions. No consistent decrease in reflected light intensity could be seen during coagulation of white matter. Clinical measurements were performed during the creation of 21 trajectories for deep brain stimulation electrodes. In agreement with the simulations, reflected light intensity was found to differentiate well between undamaged grey, light grey and white matter.   In conclusion, blood perfusion and CSF in particular may greatly affect the lesioning process and can be important to consider when planning surgery. Reflected light intensity seems unreliable for the detection of coagulation in light grey brain matter such as the thalamus. However, it seems very promising for navigation in the brain and for detection of coagulation in other tissue types such as muscle.

This thesis is about simulation of semiconductor X-ray and particledetectors. The simulation of a novel coating for solid state neutrondetectors is discussed as well as the implementation of a simulationframework for hybrid pixel detectors.Today’s most common thermal neutron detectors are proportionalcounters, that use 3He gas in large tubes or multi wire arrays. Globalnuclear disarmament and the increase in use for homeland securityapplications has created a shortage of the gas which poses a problemfor neutron spallation sources that require higher resolution and largersensors. In this thesis a novel material and clean room compatible pro-cess for neutron conversion are discussed. Simulations and fabricationhave been executed and analysed in measurements. It has been proventhat such a device can be fabricated and detect thermal neutrons.Spectral imaging hybrid pixel detectors like the Medipix chipare the most advanced imaging systems currently available. Thesechips are highly sophisticated with several hundreds of transistors perpixel to enable features like multiple thresholds for noise free photoncounting measurements, spectral imaging as well as time of arrivalmeasurements. To analyse and understand the behaviour of differentsensor materials bonded to the chip and to improve development offuture generations of the chip simulations are necessary. Generally, allparts of the detector system are simulated independently. However, itis favourable to have a simulation framework that is able to combineMonte Carlo particle transport, charge transport in the sensor as wellas analogue and digital response of the pixel read-out electronics. Thisthesis aims to develop such a system that has been developed withGeant4 and analytical semiconductor and electronics models. Further-more, it has been verified with data from measurements with severalMedipix and Timepix sensors as well as TCAD simulations.Results show that such a framework is feasible even for imagingsimulations. It shows great promise to be able to be extended withfuture pixel detector designs and semiconductor materials as well asneutron converters to aim for next generation imaging devices.

The study seeks to determine the effect upon the F-statistic of violating the assumption of homogeneity of regression slopes in the one-way, fixed-effects analysis of covariance model. The study employs a Monte Carlo simulation technique to vary the degree of heterogeneity of regression slopes with varied sample sizes within experiments to determine the effect of such conditions. One hundred and eighty-three simulations were used.

The efficient market hypothesis is one of the most important propositions in finance theory and has been subjected to years of rigorous empirical testing. We examine power of a new tool for evaluating market efficiency, fractal dimension. Characteristics and abilities of fractal dimension measure are explored through extensive Monte Carlo simulations. We prove that it provides an accurate evaluation of market's efficiency and its changes. This approach is highly innovative and creates new possibilities for examination of markets. The uniqueness of fractal dimension is in its ability to assign a numerical ranking to examined series describing the level of (in)efficiency; it is accurate for small samples of observations and quickly reflects changes in market efficiency structure. Powered by TCPDF (www.tcpdf.org)

English The thesis explores the topic of cost planning of Public-Private-Partnership (PPP) projects in the Czech Republic, especially with respect to institutional settings and road infrastructure. First, the PPP concept is introduced from a theoretical perspective and compared to traditional public procurement. Then the financing of PPP projects is discussed in the context of project finance and the European PPP market. The main part of the thesis focuses on public procurement of road infrastructure and the advantages of the PPP organizational structure. Initially, flaws of the procurement institutions are identified and a number of solutions suggested. The solutions cover four main areas: improvement of procurement laws, better qualifications of public officials, strategic planning of needed roads and asset management perspective on the existing infrastructure. The question whether Czech institutions are hindering the potential of PPP projects is answered positively. Follows a thorough empirical analysis of a World Bank PPP model for highways through a Monte Carlo simulation. A particular case of R35 motorway is evaluated as a PPP project and key drivers of public and private NPV are identified and compared across three different scenarios. Heavyweight traffic intensity, its toll revenue and...