This study investigated the discrimination between sources of the semi-precious mineral, nephrite, by a targeted microanalytical determination of the elemental composition, including the trace elements. Nephrite specimens were collected from two significant nephrite sources in New Zealand, namely the Westland and Wakatipu fields, and combined with donated specimens from the Southland field to complete a representative collection of New Zealand nephrite. A small number of nephrite specimens were donated from the South Westland nephrite field and from foreign sources. Representative fragments of these specimens were analysed by electron microprobe analysis (EMPA) for major elements and by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for trace elements. The data obtained by the analytical procedure were treated within a compositional data (CoDa) framework of statistical analysis that focuses on the relative sizes of the components in the data set. The data were transformed under the guidelines of the CoDa framework, where appropriate, and the transformed data were treated with standard statistical methods for exploratory data analysis, dimension reduction and discriminant analysis. Advances were made to the Hotelling’s method for comparison of multivariate means by incorporating a permutation evaluation step. This permutation method removes the requirement for multivariate normality, and it also allows comparisons to be made when there are many more variables than observations, as is often the case when objects are being characterized using elemental data. The strategy used in this study showed that it is possible to discriminate between sources of nephrite at both an intra- and inter-source level within New Zealand. In addition, an exploratory investigation showed that New Zealand nephrite could be differentiated from the few nephrite specimens from foreign sources that were available for comparison. Recommendations are made for the protection of the New Zealand nephrite resource and for casework, based on the results obtained in this study.

R Coronae Borealis (RCB) stars belong to a rare class of variable stars characterized by sudden and unpredictable declines, which are believed to be caused by dust cloud obscuration. In spite of the fact that these stars are so rare (only about 40 are known in our Galaxy), there are many reasons for investigating them. The unusual variability and peculiar chemical composition make them unique among all known types of variable stars. Their evolution and the nature of their unpredictable minima are still not entirely understood. Very few observations of RCB stars during the decline phase exist. Only three RCB stars (R CrB, RY Sgr and V854 Cen) have been studied in detail and only a few declines have been completely covered by observations. This thesis investigates the spectroscopic and photometric characteristics of RCB variables during their decline phases. A programme of photometric and spectroscopic observations of nine RCB and three HdC stars has been undertaken at Mt John University Observatory (MJUO) over a period of two and a half years. The programme includes some typical examples of RCB stars (Teff ~ 7000 K), as well as some cool ones (Teff ~ 5000 K). One of the most unusual of all RCB stars, V854 Cen, is also included. The photometric observations, as part of the long-term monitoring of RCB stars at MJUO, have provided the UBVRIphotometry and have served as a decline indicator. Complex colour changes during the declines were monitored and compared with the spectroscopy. The photometry during the recovery phases of the nine RCB stars in the last 12 years was used for studying the extinction properties of the gas obscuring the photosphere. An analysis of 26 different declines shows that the material causing the declines has extinction properties similar to those of the interstellar medium. The medium and high-resolution spectroscopy has been obtained for six declines of different programme stars using the 1-m telescope at MJUO. Although the duration and depth of the declines are very different, they all show similar photometric and spectroscopic characteristics. The results have been compared with other observations and used to examine a simple line-region model (E1/E2/BL), which attempts to describe the evolution and origin of emission lines during a decline. In general, the evolution of various emission lines observed in this work is consistent with their classification into these three groups. However, some characteristics of the emission lines indicate a different origin from that suggested by the model. A very rich emission line spectrum was monitored during the 1998 decline of V854 Cen, while only the most prominent lines were observed in the other stars. Short-lived high-excitation lines from the initial decline phase, such as CI and 01, were classified as Ei. They show a characteristic, shock-induced red shift indicating the photospheric origin. Lines classified as E2 are mainly from the low-excitation ions and neutral atoms. All lines from this group appear at the very beginning of the decline and are visible through to the late recovery phase, slightly blue-shifted relative to the stellar velocity. The lines of the low-excitation ions exhibit a complex structure with a strong central and two weaker components, one on each side. Their absolute flux evolution has been compared with the changes in the stellar continuum flux. The behaviour of these lines indicates that they are not affected by the dust cloud in the same way as the photospheric continuum. Assuming that the dust cloud is formed at about 2R* and taking into account the acceleration obtained from the analysis of the high-velocity Nal D absorption lines, the position of the E2 line emitting region was estimated to be about 3R* - 5R*. The third group (BL) consists of broad emission lines, which are a typical feature of all observed declines. The most prominent broad lines present in all RCB stars belong to the Nal D doublet. The observations demonstrate that these lines are the strongest in V854 Cen, due to the significant amount of material produced by its frequent declines. In contrast to the E2 lines, whose fluxes have been found to decrease during the decline, the absolute flux of the broad lines stays constant throughout the whole decline phase. This is consistent with the idea that the broad emission is a permanent feature, whose visibility depends only on the photospheric brightness. Various Nal D components (sharp and broad emission and high-velocity absorption) have been analysed in a number of RCB declines and presented in this thesis. The high-velocity blue-shifted Nal D absorption demonstrates similar velocities (between -230 kms-1 and -400 kms-1), structure and behaviour in the different declines. The observations from the 1998 decline of V854 Cen clearly show that the high-velocity absorption lines can also appear during the initial decline phase. This suggests that they can be associated with the clouds formed in some previous declines, as well as with the current one. The spectroscopic observations of the 1998 decline of V854 Cen obtained in this thesis represent the first almost complete coverage of a decline of this star.

This thesis presents a modification of existing entropy-based splitting criteria for classification and regression trees. Trees are typically grown using splitting criteria that choose optimal splits without taking future splits into account. This thesis examines localised splitting criteria that are based on local averaging in regression trees or local proportions in classification trees. The use of a localised criterion is motivated by the fact that future splits result in leaves that contain local observations, and hence local deviances provide a better approximation of the deviance of the fully grown tree. While most recent research has focussed on tree-averaging techniques that are aimed at taking a moderately successful splitting criterion and improving its predictive power, this thesis concentrates on improving the splitting criterion. Use of a localised splitting criterion captures local structures and enables later splits to capitalise on the placement of earlier splits when growing a tree. Using the localised splitting criterion results in much simpler trees for pure interaction data (data with no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced using a global splitting criterion when applied to real data sets with strong interaction effects. The superiority of the localised splitting criterion can persist when multiple trees are grown and averaged using simple methods. Although a single tree grown using the localised splitting criterion can outperform tree averaging using the global criterion, generally improvements in predictive performance are achieved by utilising the localised splitting criterion's property of detecting local discontinuities and averaging over sets of trees grown by placing splits where the deviance is locally minimal. Predictive performance improves further when the degree of localisation of the splitting criterion is randomly selected and weighted randomisation is used with locally minimal deviances to produce sets of trees to average over. Although state of the art methods quickly average very large numbers of trees, thus making the performance of the splitting criterion less critical, predictive performance when the localised criterion is used in bagging indicates that different splitting methods warrant investigation. The localised splitting criterion is most useful for growing one tree or a small number of trees to examine structure in the data. Structurally different trees can be obtained by simply splitting the data where the localised splitting criterion is locally optimal.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 438-442).

Thesis (M.Sc.). / Written for the Dept. of Mathematics and Statistics. Title from title page of PDF (viewed 2008/12/07). Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1982. / Typescript. Vita. Description based on print version record. Includes bibliographical references (leaves 126-131).

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (p. 257-261).

Doctor of Philosophy / Department of Physics / Timothy A. Bolton / I measure a large set of observables in inclusive charged current muon neutrino scattering on argon with the MicroBooNE liquid argon time projection chamber operating at Fermilab. I evaluate three neutrino interaction models based on the widely used GENIE event generator using these observables. The measurement uses a data set consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2016 with the Fermilab Booster Neutrino Beam, which has an average neutrino energy of 800 MeV, using an exposure corresponding to 5e19 protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction and uses a data-driven technique to separate neutrino interactions from cosmic ray background events. I find that GENIE models consistently describe the shapes of a large number of kinematic distributions for fixed observed multiplicity, but I show an indication that the observed multiplicity fractions deviate from GENIE expectations.

This thesis considers the tasks involved in exploratory analysis of temporal graph data, and the visual techniques which are able to support these tasks. There has been an enormous increase in the amount and availability of graph (network) data, and in particular, graph data that is changing over time. Understanding the mechanisms involved in temporal change in a graph is of interest to a wide range of disciplines. While the application domain may differ, many of the underlying questions regarding the properties of the graph and mechanism of change are the same. The research area of temporal graph visualisation seeks to address the challenges involved in visually representing change in a graph over time. While most graph visualisation tools focus on static networks, recent research has been directed toward the development of temporal visualisation systems. By representing data using computer-generated graphical forms, Information Visualisation techniques harness human perceptual capabilities to recognise patterns, spot anomalies and outliers, and find relationships within the data. Interacting with these graphical representations allow individuals to explore large datasets and gain further insightinto the relationships between different aspects of the data. Visual approaches are particularly relevant for Exploratory Data Analysis (EDA), where the person performing the analysis may be unfamiliar with the data set, and their goal is to make new discoveries and gain insight through its exploration. However, designing visual systems for EDA can be difficult, as the tasks which a person may wish to carry out during their analysis are not always known at outset. Identifying and understanding the tasks involved in such a process has given rise to a number of task taxonomies which seek to elucidate the tasks and structure them in a useful way. While task taxonomies for static graph analysis exist, no suitable temporal graph taxonomy has yet been developed. The first part of this thesis focusses on the development of such a taxonomy. Through the extension and instantiation of an existing formal task framework for general EDA, a task taxonomy and a task design space are developed specifically for exploration of temporal graph data. The resultant task framework is evaluated with respect to extant classifications and is shown to address a number of deficiencies in task coverage in existing works. Its usefulness in both the design and evaluation processes is also demonstrated. Much research currently surrounds the development of systems and techniques for visual exploration of temporal graphs, but little is known about how the different types of techniques relate to one another and which tasks they are able to support. The second part of this thesis focusses on the possibilities in this area: a design spaceof the possible visual encodings for temporal graph data is developed, and extant techniques are classified into this space, revealing potential combinations of encodings which have not yet been employed. These may prove interesting opportunities for further research and the development of novel techniques. The third part of this work addresses the need to understand the types of analysis the different visual techniques support, and indeed whether new techniques are required. The techniques which are able to support the different task dimensions are considered. This task-technique mapping reveals that visual exploration of temporalgraph data requires techniques not only from temporal graph visualisation, but also from static graph visualisation and comparison, and temporal visualisation. A number of tasks which are unsupported or less-well supported, which could prove interesting opportunities for future research, are identified. The taxonomies, design spaces, and mappings in this work bring order to the range of potential tasks of interest when exploring temporal graph data and the assortmentof techniques developed to visualise this type of data, and are designed to be of use in both the design and evaluation of temporal graph visualisation systems.

This thesis discusses various large multi-dimensional dataset analysis methods and their applications. Particular attention is paid to non-linear optimization analyses and general processing algorithms and frameworks when the datasets are significantly larger than the available computer memory. All new presented algorithms and frameworks were implemented in the HyperSpy analysis toolbox. A novel Smart Adaptive Multi-dimensional Fitting (SAMFire) algorithm is presented and applied across a range of scanning transmission electron microscope (STEM) experiments. As a result, the Stark effect in quantum disks was mapped in a cathodoluminescence STEM experiment, and fully quantifiable 3D atomic distributions of a complex boron nitride core-shell nanoparticle were reconstructed from an electron energy loss spectrum (EELS) tilt-series. The EELS analysis also led to the development of two new algorithms to extract EELS near-edge structure fingerprints from the original dataset. Both approaches do not rely on standards, are not limited to thin or constant thickness particles and do not require atomic resolution. A combination of the aforementioned fingerprinting techniques and SAMFire allows robust quantifiable EELS analysis of very large regions of interest. A very large dataset loading and processing framework, “LazySignal”, was developed and tested on scanning precession electron diffraction (SPED) data. A combination of SAMFire and LazySignal allowed efficient analysis of large diffraction datasets, successfully mapping strain across an extended (ca. 1 μm × 1 μm) region and classifying the strain fields around precipitate needles in an aluminium alloy.