Testing uniformity in the univariate case has been studied by many researchers. Many papers have been published on this issue, whereas the multi-dimensional uniformity test seems to have received less attention in the literature. A new test statistic for the multi-dimensional uniformity is proposed in this thesis. The proposed test statistic can be used to test whether an underlying multivariate probability distribution differs from a multi-dimensional uniform distribution. Some important properties of the proposed test statistic are discussed. As a special case, the bivariate test statistic is discussed in detail and the critical values of test statistic are obtained. By performing Monte Carlo simulation, the power of the new test is compared with the Distance to Boundary test, which was a recently proposed statistical test for multi-dimensional uniformity by Berrendero, Cuevas and Vazquez-Grande (2006). It has been shown that the test proposed in this thesis is more powerful than the Distance to Boundary test in some cases.

The burgeoning field of nanotechnology motivates comprehensive elucidation of nanoscale materials. This thesis addresses transmission electron microscope characterisation of nanoparticle morphology, concerning specifically the crystal- lographic status of novel intermetallic GaPd2 nanocatalysts and advancement of electron tomographic methods for high-fidelity three-dimensional analysis. Going beyond preceding analyses, high-resolution annular dark-field imaging is used to verify successful nano-sizing of the intermetallic compound GaPd2. It also reveals catalytically significant and crystallographically intriguing deviations from the bulk crystal structure. So-called ‘non-crystallographic’ five-fold twinned nanoparticles are observed, adding a new perspective in the long standing debate over how such morphologies may be achieved. The morphological complexity of the GaPd2 nanocatalysts, and many cognate nanoparticle systems, demands fully three-dimensional analysis. It is illustrated how image processing techniques applied to electron tomography reconstructions can facilitate more facile and objective quantitative analysis (‘nano-metrology’). However, the fidelity of the analysis is limited ultimately by artefacts in the tomographic reconstruction. Compressed sensing, a new sampling theory, asserts that many signals can be recovered from far fewer measurements than traditional theories dictate are necessary. Compressed sensing is applied here to electron tomographic reconstruction, and is shown to yield far higher fidelity reconstructions than conventional algorithms. Reconstruction from extremely limited data, more robust quantitative analysis and novel three-dimensional imaging are demon- strated, including the first three-dimensional imaging of localised surface plasmon resonances. Many aspects of transmission electron microscopy characterisation may be enhanced using a compressed sensing approach.

As the most commonly diseased heart valve, the mitral valve (MV) has been the subject of extensive research for many years. Unfortunately, the only treatment options currently available are surgical repair and replacement. Although repair is almost always preferable to replacement, it is often underperformed due to the complexity of MV repair surgeries. Consequently, there is significant interest in generating patient-specific finite element models of the MV for the purpose of simulating mitral repairs. For practical purposes transesophageal echocardiographic (TEE) images are most commonly used to reconstruct the mitral apparatus. However, limitations in ultrasound technology have prevented the detection of leaflet thicknesses. In the current study, a method was developed to accurately model variations in leaflet thicknesses using TEE datasets. Nine healthy datasets were modeled and the leaflet thicknesses were found to closely match previously reported results. As anticipated, normal valve function was also observed over the entire cardiac cycle.

This thesis investigates the use of bromine intercalation of graphite as a method to simulate and investigate irradiation damage. In particular this study investigates the effects of intercalation on dimensional change on the macro and micro scales and how these changes combine to affect Young’s modulus. Highly Orientated Pyrolytic Graphite has been used to gather data as a close approximation to single crystal graphite. Three different grades of polycrystalline nuclear graphite have been used to investigate the effect of different microstructure on intercalation and subsequent property changes. The graphites have been characterized by optical microscopy, pycnometry and x-ray powder diffraction and texture measurements. A number of bespoke rigs were designed and manufactured to carry out sorption, tomography and laser vibrometry experiments.The results indicate that the rate of dimensional change for polycrystalline graphites is significantly lower than for single crystal graphites. Modelling of dimensional change suggests that the difference in expansion is due to closure of porosity. Closer investigation of the dimensional change within the microstructure shows that the majority of the dimensional change is driven by expansion of filler particles.The young’s modulus results show an initial increase in modulus followed by a decrease, which corresponds with empirical evidence for irradiated samples. It is postulated that the initial increase in modulus is due to crystal expansion and that the subsequent decrease is due to crack growth. After experimentation some samples show significant cracking which would appear to support this assertion.

For nearly a decade, quasi-one-dimensional conductors have been the subject of intensive study. Theoretically, much attention has been devoted to the development of one-dimensional Fermi gas models, some which may be solved exactly, and to the calculation of their response functions. After a review of this theory, a different approach is adopted in the investigation of two models. The dielectric response theory of the three-dimensional Coulomb gas has been applied to an anisotropic system in which the particles interact with an effective one-dimensional long-range potential. Within the framework of the approximation of Singwi, Tosi, Land, and Sjolander, the dielectric properties of the model are examined in order to determine the conditions under which it is unstable with respect to formation of a charge density wave state. It is found that the positive neutralizing background must be polarizable in order for such an instability to occur. The same approximation method, when applied to a one-dimensional fermion gas with a ʃ-function interaction may be compared with the exact solution of Yang. This solution, which exists in the form of coupled integral equations, has been calculated numerically, and, as predicted by the Lieb-Mattis theorem, the ground state is found to be non-magnetic. The approximation of Singwi et al. proves to give better correlation energies than other inexact methods, particularly at higher densities. / Science, Faculty of / Physics and Astronomy, Department of / Graduate

Previous research suggests there are a number of variables that are associated with the expression of schizotypal personality disorder (SPD) symptoms. Such variables include childhood trauma, depression and anxiety, substance use, normal-range personality traits, ethnicity, and gender. However, research to date has not examined all of these variables in a single study to determine how they may be interrelated or differentially related to SPD symptom domains. Of particular interest is the association of these variables as explained by the diathesis-stress model. This study utilized a convenience sample of 298 undergraduate students to examine a continuous range of scores for symptoms of SPD and how the interrelation of biological factors such as gender and ethnicity and psychosocial factors and stressors such as childhood trauma and personality traits, specifically neuroticism and extroversion, influence the expression of SPD symptoms. It was predicted that anxiety, depression, stress, and childhood trauma would positively correlate to SPD symptoms. It was also hypothesized that neuroticism and substance use would positively correlate to schizotypal traits and extroversion would be negatively correlated to schizotypal traits as measured by the Schizotypal Personality Questionnaire-Brief. It was further hypothesized that psychosocial stressors would be moderated by the aforementioned biological factors.

Fault detection and diagnosis presents a big challenge within the petrochemical industry. The annual economic impact of unexpected shutdowns is estimated to be $20 billion. Assistive technologies will help with the effective detection and classification of the faults causing these shutdowns. Clustering analysis presents a form of unsupervised learning which identifies data with similar properties. Various algorithms were used and included hard-partitioning algorithms (K-means and K-medoid) and fuzzy algorithms (Fuzzy C-means, Gustafson-Kessel and Gath-Geva). A novel approach to the clustering problem of time-series data is proposed. It exploits the time dependency of variables (time delays) within a process engineering environment. Before clustering, process lags are identified via signal cross-correlations. From this, a least-squares optimal signal time shift is calculated. Dimensional reduction techniques are used to visualise the data. Various nonlinear dimensional reduction techniques have been proposed in recent years. These techniques have been shown to outperform their linear counterparts on various artificial data sets including the Swiss roll and helix data sets but have not been widely implemented in a process engineering environment. The algorithms that were used included linear PCA and standard Sammon and fuzzy Sammon mappings. Time shifting resulted in better clustering accuracy on a synthetic data set based on than traditional clustering techniques based on quantitative criteria (including Partition Coefficient, Classification Entropy, Partition Index, Separation Index, Dunn’s Index and Alternative Dunn Index). However, the time shifted clustering results of the Tennessee Eastman process were not as good as the non-shifted data. Copyright / Dissertation (MEng)--University of Pretoria, 2009. / Chemical Engineering / unrestricted

A eletrônica molecular vem sendo investigada intensivamente por mais de vinte anos. Nesse sentido, as pesquisas científicas estão sendo focadas na busca de estruturas que possam ser utilizadas na construção de dispositivos em escalas nanométricas, que possam substituir a tecnologia tradicional do silício. O objetivo principal deste trabalho foi explorar as propriedades físicas de sistemas a base de grafano, um dos mais promissores materiais para serem usados como nanodispositivos. Para isso, foi realizada uma investigação teórica, baseada em cálculos de primeiros princípios, das propriedades estruturais e eletrônicas do grafeno numa forma pura ou com defeitos intrínsecos e extrinsecos. O primeiro grupo de estruturas investigadas foi o grafeno e grafano como nanofolhas constituídas por elementos do grupo IV da tabela periódica (C, SiC, Si, Ge e Sn). Também foram analisadas as mudanças nas propriedades eletrônicas do grafano do grupo IV com a substituição dos átomos de hidrogênio por flúor. A segunda parte do trabalho explorou as propriedades de defeitos estruturais em grafeno, tais como a monovacância, divacância, trivacância e Stone-Wales, e também o grafeno com dopantes (boro e nitrogênio) em diversas configurações. Todos os cálculos foram feitos utilizando métodos ab initio com base na teoria do funcional densidade. Foram estudadas algumas possíveis aplicações para os grupos de estruturas de grafeno investigados, através da análise de algumas de suas propriedades, tais como as densidades de estados próximas ao nível de Fermi e as estruturas de bandas eletrônicas para cada sistema. / The molecular electronics has been investigated for more than twenty years. In this sense, the scientific research has been focused on the search for structures that could be used in nanoelectronic devices that could replace the traditional silicon technology. The major goal of this work is to explore the physical properties of systems based on graphene, one of the most promising materials to be used in nanoelectronics. For that, an ab initio investigation was carried on the structural and electronic properties of graphene in its pristine form and with intrinsic and extrinsic defects. The first investigation explored the properties of group IV nanosheets (of C, SiC, Si, Ge e Sn), and the modifications on their properties as result of hydrogenation or fluorination. The second part of this work explored the physical properties of structural intrinsic defects in graphene, such as monovacancy, divacancy, trivacancy, and Stone-Wales ones. The work also explored the properties of boron and nitrogen dopants. All the calculations were performed using the ab initio methodology, based on the density functional theory.

archives@tulane.edu / Modern biomedical studies often collect multiple types of high-dimensional data on a common set of objects. A representative model for the integrative analysis of multiple data types is to decompose each data matrix into a low-rank common-source matrix generated by latent factors shared across all data types, a low-rank distinctive-source matrix corresponding to each data type, and an additive noise matrix. We propose a novel decomposition method, called the decomposition-based generalized canonical correlation analysis, which appropriately defines those matrices by imposing a desirable orthogonality constraint on distinctive latent factors that aims to sufficiently capture the common latent factors. To further delineate the common and distinctive patterns between two data types, we propose another new decomposition method, called the common and distinctive pattern analysis. This method takes into account the common and distinctive information between the coefficient matrices of the common latent factors. We develop consistent estimation approaches for both proposed decompositions under high-dimensional settings, and demonstrate their finite-sample performance via extensive simulations. We illustrate the superiority of proposed methods over the state of the arts by real-world data examples obtained from The Cancer Genome Atlas and Human Connectome Project. / 1 / Zhe Qu

This experiment investigated the effect of infill pattern shape on structural stiffness for 3D printed components made out of carbon fiber reinforced nylon. In order to determine the natural frequency of each specimen, nondestructive vibrational testing was conducted and processed using data acquisition software. After obtaining the acceleration information of each component, in response to ambient vibrational conditions and excitation, frequency response functions were generated. These functions provided the natural frequency of each component, making it possible to calculate their respective stiffness values. The four infill patterns investigated in this experiment were: Zig Zag, Tri-Hex, Triangle, and Concentric. Results of the experiment showed that changing the infill pattern of a 3D printed component, while maintaining a constant geometry and density, could increase mechanical stiffness properties by a factor of two. Comprehensively, the experiment showed that infill pattern geometry directly attributes to the mechanical stiffness of 3D printed components. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection