Improving Reproducibility whilst Maintaining Accuracy in Function Point Analysis

Existing proposals to improve the measurement reproducibility of Function Point Analysis (FPA) oversimplify its standard rules, threatening its measurement accuracy. We introduce a new artifact called Function Point Tree (FPT), which allows for full data collection required to count function points, reducing the experts’ personal interpretation and thus the size variation. The new measurement method, called FPT-based FPA (FPT-FPA), enlarges FPA standardization and systematization. Using this method allows to improve measurement reproducibility whilst maintaining its accuracy. Preliminary results of an empirical study show coefficients of variation for FTP-FPA lower than the maximum expected for both reproducibility and accuracy for some scenarios

Magnetic resonance imaging of lung cancer in the presence of respiratory motion: Dynamic keyhole and audio visual biofeedback

Breath-to-breath variations in breathing can cause image artefacts. Day-to-day variations can cause a disagreement of position and volume between planning and treatment throughout radiotherapy procedures, requiring a larger treatment margin and longer treatment time. An advanced radiotherapy system requires: (1) a fast imaging technique for the compensation of breathing variations and/or (2) a respiratory motion management technique for the control of breathing variations. A novel MRI reconstruction method called “Dynamic keyhole” was proposed as a fast imaging technique. This thesis investigated (1) the concept of this method in terms of the improvement in temporal resolution with healthy volunteer MRI datasets and (2) the applicability of real-time lung tumour localization in terms of the accuracy of tumour motion and shape with lung cancer patient MRI datasets. The dynamic keyhole method achieved an increase in imaging frequency by up to a factor of five when compared with full k-space methods whilst achieving sub-millimetre tumour motion accuracy and preserving tumour shape within 98%. AV biofeedback respiratory guidance was used for healthy volunteers and lung cancer patients. This thesis investigated the impact of AV biofeedback on (1) intra- and inter-fraction lung tumour motion using cine-MRI, (2) inter-fraction lung tumour position and intra-fraction tumour volume using breath-hold MRI and (3) the improvement in image quality and the reduction in scan time using respiratory-gated MRI. AV biofeedback respiratory guidance improved intra- and inter-fraction tumour motion and position reproducibility, and intra-fraction tumour volume consistency. In addition, it was found to improve image quality and reduce scan time. The performance of the dynamic keyhole method and AV biofeedback respiratory guidance shown in this thesis illustrates potential advantages of real-time tumour imaging and tumour motion management in the course of lung cancer radiotherapy

Multivariate spectral analysis of pH SERS probes for improved sensing capabilities

Appropriate functional groups adsorbed to the surface of plasmonic nanoparticles provides a platform for localised optical sensing. For example, intracellular pH nanosensors based on surface enhanced Raman spectroscopy (SERS) have been developed. However, the measurement methods and analysis of pH-SERS can greatly impact the precision and accuracy of pH calibration. This paper provides several key improvements to the performance and analysis pH nanosensors which thus transforms the performance into a useable intracellular pH sensor. We report the plasmon-induced decarboxylation of para-mercaptobenzoic acid (pMBA) pH-reporters which are bound to the gold nanoparticles, and attribute this to the laser power. This detrimental decarboxylation of pMBA has significant implications for accurate reporting and analysis due to the sensitivity and reliability of the pH sensor. The greatest implication of decarboxylation of pH sensors is inaccurate or false pH reporting, because the decarboxylation spectral signatures map directly onto those that are typically used to record pH changes. Here a unique application of the multivariate statistical technique, principal components analysis (PCA) is presented along with an optimal spectral region for pH calibration. By direct comparisons between the PCA method with the typically employed ratio-metric analysis a significant improvement in generating accurate pH sensing is demonstrated. An application of intracellular pH sensing in macrophage cells using these nanosensors promotes these step-changes in pH measurement methodology

Ancestry-independent osteometric sex estimation from selected postcranial skeletal elements of South Africans: a machine learning approach

Sex estimation, as part of a biological profile, has the power to halve the number of possible identities of unidentified skeletal remains. Postcranial elements have been studied in South Africa (SA) for the purpose of sex estimation and have often proven to be more accurate than the cranium. Estimation techniques using postcranial elements in SA almost exclusively utilise discriminant analysis to evaluate sex, but international publications have shown success using alternative machine learning (ML) algorithms. SA methods and standards are often restricted by limited sample size, lack of robust statistical techniques in older publications and, the prerequisite of known or estimated ancestry. Most methods are specific to SA African, European or, more recently, Mixed ancestry groups and are unreliable when ancestry is unknown. The aim of this study was to apply a series of ML algorithms to train ancestry independent sex classification models using postcranial osteometric measurements from the cadaveric skeletal remains of modern South Africans, focussing on long bone joints. The study consisted of a roughly demographically representative, pooled sample, of 650 South Africans (325 male, 325 female). 12 osteometric measurements were taken from available left- and, or right-sided bones for each individual. All 12 mensurations were sexually dimorphic and differences between left- and right-sided bones were negligible. The dataset was subjected to ML algorithm training using univariate and multivariate predictor combinations. The best performing ML algorithm, given the sample size and available predictors was discriminant function analysis. Univariate model accuracies ranged from 80.5-89.1% and multivariate model accuracies ranged from 84.5%, using 2 predictors, to 92.8%, using 12 predictors. An optimised 3-predictor model was able to predict sex with 92.7% accuracy. Results from this study were comparable to those using ancestry-specific models and non-ancestry-specific models, where available. Findings from this study suggest that the inclusion of ancestry, when predicting sex using the elements examined, is not necessary as it does not significantly improve prediction accuracy

Accelerated internal resistance measurements of lithium-ion cells to support future end-of-life strategies for electric vehicles

Industrial and academic communities have embarked on investigating the sustainability of vehicles that contain embedded electrochemical energy storage systems. Circular economy strategies for electric vehicle (EV) or hybrid electric vehicle (HEV) battery systems are underpinned by implicit assumptions about the state of health (SOH) of the battery. The internal resistance of battery systems is the essential property for determining available power, energy efficiency, and heat generation. Consequently, precise measurement is crucial to estimate the SOH; however, the international standards and best practice guides that exist to define the measurements include long preconditioning and rest times that make the test duration prohibitive. The aim of this research is to critically evaluate whether test duration times for internal resistance measurements can be reduced to values that may facilitate further end-of-life (EOL) options. Results reveal a newly developed technique using pulse-multisines is two to four times faster to perform when compared to the standard protocol whilst maintaining accuracy for battery electric vehicle (BEV) and HEV cells, respectively. This novel method allows different stakeholders to rank the relative importance of test accuracy verses experimental test time when categorising used Li-ion cells for different EOL applications. View Full-Tex