Providence, Emotion and Self-Writing in England, c.1660 – c.1720

This thesis offers a new interpretation of providentialism in late seventeenth- and early eighteenth-century England. Historians have seen this as a transitional period in providential belief and expression, between heightened engagement and gradual decline, and have provided us with many perspectives on the changing role of providence in English culture. But we still have yet to understand fully the role of providence in individual lives, where change occurred at an experiential and quotidian level. This thesis aims to fill this historiographical gap by examining practical, subjective and individual experiences of providentialism. Drawing on first-person narratives such as diaries and memoirs, conceptualised as sites of personal agency, it sheds light at the micro-level on broader shifts in providential belief and thought. These primary sources show how individuals exercised a personal providentialism, writing their relationship with God’s providence into their own emerging sense of self. Investigation of the emotional resonances of providentialism also emphasizes its centrality to inner lives and personal identity, characterised by subtle but significant modes of feeling. Several case studies demonstrate how people constantly shaped and re-shaped themselves, and moulded ideas and beliefs relating to providence to fit particular social and religious circumstances and changing intellectual concerns. Providentialism is therefore shown to be elastic and subjective – a subjectivity that ensured the adaptability and durability of the concept of providence in an era of atheism, science and expanding secular authority. Far from seeing this period as a stage in an inexorable decline, the thesis shows how people continued to find uses for providence in creative and imaginative ways to make sense of themselves and their world in the late seventeenth and early eighteenth centuries

Statistical Approaches to Inferring Object Shape from Single Images

Depth inference is a fundamental problem of computer vision with a broad range of potential applications. Monocular depth inference techniques, particularly shape from shading dates back to as early as the 40's when it was first used to study the shape of the lunar surface. Since then there has been ample research to develop depth inference algorithms using monocular cues. Most of these are based on physical models of image formation and rely on a number of simplifying assumptions that do not hold for real world and natural imagery. Very few make use of the rich statistical information contained in real world images and their 3D information. There have been a few notable exceptions though. The study of statistics of natural scenes has been concentrated on outdoor scenes which are cluttered. Statistics of scenes of single objects has been less studied, but is an essential part of daily human interaction with the environment. Inferring shape of single objects is a very important computer vision problem which has captured the interest of many researchers over the past few decades and has applications in object recognition, robotic grasping, fault detection and Content Based Image Retrieval (CBIR). This thesis focuses on studying the statistical properties of single objects and their range images which can benefit shape inference techniques. I acquired two databases: Single Object Range and HDR (SORH) and the Eton Myers Database of single objects, including laser-acquired depth, binocular stereo, photometric stereo and High Dynamic Range (HDR) photography. I took a data driven approach and studied the statistics of color and range images of real scenes of single objects along with whole 3D objects and uncovered some interesting trends in the data. The fractal structure of natural images was previously well known, and thought to be a universal property. However, my research showed that the fractal structure of single objects and surfaces is governed by a wholly different set of rules. Classical computer vision problems of binocular and multi-view stereo, photometric stereo, shape from shading, structure from motion, and others, all rely on accurate and complete models of which 3D shapes and textures are plausible in nature, to avoid producing unlikely outputs. Bayesian approaches are common for these problems, and hopefully the findings on the statistics of the shape of single objects from this work and others will both inform new and more accurate Bayesian priors on shape, and also enable more efficient probabilistic inference procedures

Modelling of Information Flow and Resource Utilization in the EDGE Distributed Web System

The adoption of Distributed Web Systems (DWS) into modern engineering design process has dramatically increased in recent years. The Engineering Design Guide and Environment (EDGE) is one such DWS, intended to provide an integrated set of tools for use in the development of new products and services. Previous attempts to improve the efficiency and scalability of DWS focused largely on hardware utilization (i.e. multithreading and virtualization) and software scalability (i.e. load balancing and cloud services). However, these techniques are often limited to analysis of the computational complexity of the algorithms implemented. This work seeks to improve the understanding of efficiency and scalability of DWS by modelling the dynamics of information flow and resource utilization by characterizing DWS workloads through historical usage data (i.e. request type, frequency, access time). The design and implementation of EDGE is described. A DWS model of an EDGE system is developed and validated against theoretical limiting cases. The DWS model is used to predict the throughput of an EDGE system given a resource allocation and workflow. Results of the simulation suggest that proposed DWS designs can be evaluated according to the usage requirements of an engineering firm, ultimately guiding an informed decision for the selection and deployment of a DWS in an enterprise environment. Recommendations for future work related to the continued development of EDGE, DWS modelling of EDGE installation environments, and the extension of DWS modelling to new product development processes are presented

The Use of Celebrity and Non-celebrity Examples to Reduce Stigma in University Students

Although effective treatments have been developed for various mental illnesses, many individuals who need psychological help do not seek it because of stigma. Interventions have been developed to reduce stigma, with the hope of increasing access to mental healthcare. Vicarious contact with individuals who have mental illness can reduce both public and internal stigma. Furthermore, celebrity examples have been used to reduce stigma. The present study compared celebrity examples and non-celebrity examples across a stigma-reduction intervention, as well as a control group, to determine the most effective ways to present first-person narrative vignettes for reducing both public and internal stigma. The results showed that exposure to celebrity status in the form of a vignette did not statistically significantly reduce self-reported scores for either public or internal stigma, on average, when compared to exposure to a non-celebrity or no exposure (a control group)