The thesis provides a well-researched classical approach to fit and predict the losses (extreme) for Lloyds Bank’s Dutch mortgage portfolio, their defaulted Dutch mortgage portfolio, and their German personal and car loan portfolio. This is a crucial piece for quantification of the economic loss, required for effective credit risk management by the Bank. For starters, the distribution of losses needs to be defined in order to determine the amount of losses that a bank can possibly experience in an event that corresponds to a specific confidence level. To get to that point, the data needs to be approximated with either one or more distributions, this thesis covers the single distribution approach and the mixture model approach that uses two distributions to solve the approximation of the data. Our work concludes that the optimal distribution for the regular Dutch mortgage portfolio losses include a Beta-Beta mixture and a Lognormal-Gamma mixture. Where the Lognormal-Gamma mixture has utilized a threshold approach that splits the data into two separate data sets and then fits the data separately before combining them with a weight function. While, for the second Dutch mortgage portfolio at the specific snapshots, the Beta and the Generalized Pareto outperformed the rest. Furthermore, for the German personal and car loan portfolio, the Generalized Pareto also performed the best. This is a crucial step for calculating the necessary economic capital that Lloyds Banking Group plans to do in the near future.

The purpose of this paper is to examine the interactions between two plant species endemic to Florida and develop a model for the growth of one of the plant species. An equation for the growth of Hypericum cumulicola is developed through analyzing how the distance to and the height of the nearest Ceratiola ericoides (Florida rosemary) affects the growth of Hypericum cumulicola. The hypericums were separated into five separate regions according to the distance to the nearest rosemary plant. The parameters for a basic growth equation were obtained in each of the five regions and compared to each other along with the average deviations in each of the five regions. Analysis of the five separate regions aided in the creation of different growth equations that each encompassed all of the regions together. Four different growth equations are developed and then compared and analyzed for their accuracy.

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The last five years have shown us the profound impact that SARS-CoV-2 pandemic has had on human kind and made us aware of the dangers that emerging pathogens can present. The goal of this dissertation is to use mathematical models in connection with data to uncover mechanistic interactions governing viral infections. To acquire a holistic understanding of the impact of viral infections, it is necessary to develop mathematical techniques and models that bridge knowledge on multiple biological scales. This dissertation explores the relationship between within-host virus dynamics, the environment and the between-host viral transmission. We will validate the models against data from SARS-CoV-2 infections, and data from infections with an emerging pathogen, the Usutu virus. Our models of SARS-CoV-2 infection looked at the relationship between infectious virus and viral RNA in the body and in the environment. Using golden hamster data and within-host mathematical models, we determined that infectious virus shedding early in infection correlates with transmission events, shedding of infectious virus diminishes late in the infection, and high viral RNA levels late in the infection are a poor indicator of transmission. We further showed that viral infectiousness increases in a density dependent manner with viral RNA and that their relative ratio is time-dependent. Such information is useful for designing interventions. Our models of Usutu virus infection looked at differences between different virus strains during bird infections. Within-host models applied to data showed heterogeneity in viral strain dynamics, and correlated high basic reproductive number with short infected cell lifespan (indicative of immune responses) and correlated low basic reproductive number with low viral peaks and longer lasting viremia (due to lower infection rates and high infected cell lifespan). We expanded the models to investigate multiscale dynamics connecting within-host scale, bird-to-vector transmission scale, and vector-borne epidemiological scale. One important direction of this dissertation is the investigation of uncertainty in parameter estimation and overall model identifiability. We conducted identifiability studies (using several theoretical tools) in the multiscale models of Usutu virus infection and in several within-host influenza models. Model identifiability is critical to the reproducibility of modeling results in any biological systems. In this dissertation, we will show how insights from such analyses inform both modeling practices and experimental design. / Doctor of Philosophy / The last five years have shown us the profound impact that SARS-CoV-2 pandemic has had on human kind and made us aware of the dangers that emerging pathogens can present. Within-host mathematical models are tools that can be used to study the dynamics of virus infections. These models help us gain an understanding of biological quantities of interest, relationships between biological processes in a quantitative and qualitative ways, and disease outcome. However, to acquire a holistic understanding of the impact of viral infections, it is necessary to develop mathematical tools and models that bridge knowledge on multiple biological scales. This dissertation explores the relationship between virus infection characteristics over time in a single host and larger biological scales including virus' release into the environment and spread of virus between hosts. Biological and public health insights about SARS-CoV-2 and Usutu virus were gained through these modeling efforts.

No / Transportation infrastructure projects are prone to cost and schedule overruns. At the time of contract award, a construction contingency budget is often used to accommodate for unplanned events such as scope changes. Recent empirical research has shown that rework during construction as a result of design changes, errors and omission are the major contributors of overruns in projects. The statistical characteristics of rework, and cost and schedule overruns that are experienced from a project's contract award for 58 Australian transportation infrastructure projects are analysed. Theoretical probability distributions are fitted to the rework, cost and schedule overrun data. Goodness of fit tests are used in conjunction with probability-probability (P-P) plots to compare the sample distribution from the known theoretical distribution. A Generalised Logistic probability density function is found to describe the behaviour of cost-overruns and provides the best overall distribution fit. The best fitting distribution for schedule overruns and rework data were the Four Parameter Burr and a Johnson SB distribution, respectively. The distributions are used to calculate the probability of rework, cost and schedule overruns being experienced. A case illustration is presented and discussed to demonstrate how the derived probabilities may be utilised in practice.

This research study presents two control solutions, PID and the novel hyper-clothoid control strategy, to autonomously navigate a car. These waypoint navigation solutions smoothly connect the given waypoints with C1 continuity using Hermite cubic splines which is used as a reference path for the controller to track. The PID controller uses lateral and heading error to generate a steering profile for the vehicle to track the constructed reference path. A novel real time solution is presented as the second control strategy which involves constructing clothoids to generate a steering profile. The resultant car trajectory preserves curvature and curvature rate continuity. A simulation test bench was developed in MATLAB and Simulink. Six benchmark waypoint datasets have been used for regression testing and validating the algorithms. Both the proposed control strategies have been implemented on a 2017 GM Chevy Bolt EV. A real time operating system (QNX) has been used and was time-synced with the localization suite in the test vehicle. Closed loop results with accuracies up to 50 cm of lateral error have been achieved using the test vehicle. / Doctor of Philosophy / The research into self-driving cars has been one of the most sought out areas these past couple of decades. There are many components into building a self-driving car - Sensing, Perception, Localization, Navigation. Lot of strategies have been developed over the years with waypoint navigation being the most widely used for navigation an autonomous vehicle. Waypoint Navigation utilizes GPS data to move the car from one point to the other. The traditional process of this strategy involves two parts - curve fitting between waypoints and using a control scheme to track the path with the car. Numerous methods have been developed to fit a curve in between two points. Most of these methods use a variant of 3rd degree or higher order polynomials . Also different control strategies have been developed to track the generated path. Model predictive control strategies are among the popular control architectures used for this purpose. This work proposes a novel method to track a path using clothoids. The proposed algorithm has a novel approach of integrating the path construction and control strategy. The algorithm also has a low computational requirement making it highly suitable for implementation in real-time.

Excerpt: As expressed in published guidelines, there are several components to the overall hearing aid fitting process. The primary focus usually surrounds the selection of the hearing aids and their special features, verification of the fitting, and then some type of real-world validation. Another component recommended in all published hearing aid fitting guidelines but often overlooked, is pre-testing.

Excerpt: What? You say you don't believe in prescriptive methods for programming hearing aids? Really? Then let me ask you this: Your Monday morning patient has a relatively flat 60 dB loss of cochlear origin. Would you program his hearing aids with 60 dB gain? Of course not. How about 10 dB gain? Not good either, right? Guess what—the moment you reached these conclusions, you're already using a prescriptive fitting approach.

Denna studie om 3D-avprovning för sport-tights är en kandidatuppsats i designteknik. Företaget studien är utvecklad för jobbar med sportkläder och har i dagsläget ett intresse av att använda sig av 3D-simulering som avprovningsmetod. Vid utveckling av tights anpassade för träning skickas i dagsläget flera prototyper mellan företaget och leverantören innan produkten kan börja produceras. För att framtagningen av produkten ska ta mindre tid, bli mer miljövänlig och kosta mindre undersöker studien om 3D-avprovning är applicerbart i företagets process för produktframtagning. För att kontrollera validiteten i 3D-avprovning av tights gjordes tre undersökningar med syfte att få förståelse för skillnaderna mellan en fysisk och en virtuell avprovning. Undersökningarna fokuserar på grundstorleken Small och den största storleken Extra Large. Studien visar att 3D-simulering till viss del är en fungerande avprovningsmetod för tights när det kommer till att kontroll av designen. För att kontrollera plaggens rörelsevidd är metoden i denna studie ej fungerande. Studiens deltagare visade en positiv inställning till att använda sig av metoden i deras produktframtagningsprocess men då främst som ett komplement till fysiska avprovningar tidigt i designprocessen. / This study on 3D fitting for sports tights is a Final Bachelor Degree Thesis in design technology. The company the study is developed for works with sportswear and currently has an interest in using 3D simulation as a fitting method. For the development of tights adapted for training, several prototypes are currently being sent between the company and the supplier before the product can start to be produced. In order for the production of the product to take less time, become more environmentally friendly and cost less, the study investigate if 3D fitting is applicable in the company's product development process. To check the validity of 3D fitting of tights, three surveys were made with the purpose of understanding the differences between physical and virtual testing. The studies focus on the base size Small and the largest size Extra Large. The study shows that 3D simulation is partially functional testing method for tights when it comes to controlling the design. In order to control the ease, the method in this study is not working. The participants of the study showed a positive attitude to use the method in their product development process, but mainly as a complement to physical fittings early in the design process.