16,596 research outputs found
Elite perceptions of the Victorian and Edwardian past in inter-war England
It is often argued by historians that members of the cultivated Elite after 1918 rejected the pre-war past. or at least subjected it to severe denigration. This thesis sets out to challenge such a view. Above all, it argues that inter-war critics of the Victorian and Edwardian past were unable to reject it even if that was what they felt inclined to do. This was because they were tied to those periods by the affective links of memory, family, and the continually unfolding consequences of the past in the present. Even the severest critics of the pre-war world, such as Lytton Strachey, were less frequently dismissive of history than ambivalent towards it. This ambivalence, it is argued, helped to keep the past alive and often to humanise it. The thesis also explores more positive estimation of Victorian and Edwardian history between the wars. It examines nostalgia for the past, as well as instances of continuity of practice and attitude. It explores the way in which inter-war society drew upon aspects of Victorian and Edwardian history both as illuminating parallels to contemporary affairs and to understand directly why the present was shaped as it was. Again, this testifies to the enduring power of the past after 1918. There are three parts to this thesis. Part One outlines the cultural context in which writers contemplated the Victorian and Edwardian past. Part Two explores some of the ways in which history was written about and used by inter-war society. Part Three examines the ways in which biographical depictions of eminent Victorians after 1918 encouraged emotional negotiation with the pas
Animating potential for intensities and becoming in writing: challenging discursively constructed structures and writing conventions in academia through the use of storying and other post qualitative inquiries
Written for everyone ever denied the opportunity of fulfilling their academic potential, this is âChloeâs storyâ. Using composite selves, a phrase chosen to indicate multiplicities and movement, to story both the initial event leading to âChloeâsâ immediate withdrawal from a Further Education college and an imaginary second chance to support her whilst at university, this Deleuzo-Guattarian (2015a) âassemblageâ of post qualitative inquiries offers challenge to discursively constructed structures and writing conventions in academia. Adopting a posthuman approach to theorising to shift attention towards affects and intensities always relationally in action in multiple âassemblagesâ, these inquiries aim to decentre individual âlecturerâ and âstudentâ identities. Illuminating movements and moments quivering with potential for change, then, hoping thereby to generate second chances for all, different approaches to writing are exemplified which trouble those academic constraints by fostering inquiry and speculation: moving away from âwhat isâ towards âwhat ifâ.
With the formatting of this thesis itself also always troubling the rigid Deleuzo-Guattarian (2015a) âsegmentary linesâ structuring orthodox academic practice, imbricated in these inquiries are attempts to exemplify Manningâs (2015; 2016) âartfulnessâ through shifts in thinking within and around an emerging PhD thesis. As writing resists organising, the verb thesisising comes into play to describe the processes involved in creating this always-moving thesis. Using âlanding sitesâ (Arakawa and Gins, 2009) as a landscaping device, freely creating emerging âlines of flightâ (Deleuze and Guattari, 2015a) so often denied to students forced to adhere to strict academic conventions, this âmovement-movingâ (Manning, 2014) opens up opportunities for change as in Manningâs (2016) âresearch-creationâ. Arguing for a moving away from writing-representing towards writing-inquiring, towards a writing âthat doesâ (Wyatt and Gale, 2018: 127), and toward writing as immanent doing, it is hoped to animate potential for intensities and becoming in writing, offering opportunities and glimmerings of the not-yet-known
Breast mass segmentation from mammograms with deep transfer learning
Abstract. Mammography is an x-ray imaging method used in breast cancer screening, which is a time consuming process. Many different computer assisted diagnosis have been created to hasten the image analysis. Deep learning is the use of multilayered neural networks for solving different tasks. Deep learning methods are becoming more advanced and popular for segmenting images. One deep transfer learning method is to use these neural networks with pretrained weights, which typically improves the neural networks performance.
In this thesis deep transfer learning was used to segment cancerous masses from mammography images. The convolutional neural networks used were pretrained and fine-tuned, and they had an an encoder-decoder architecture. The ResNet22 encoder was pretrained with mammography images, while the ResNet34 encoder was pretrained with various color images. These encoders were paired with either a U-Net or a Feature Pyramid Network decoder. Additionally, U-Net model with random initialization was also tested. The five different models were trained and tested on the Oulu Dataset of Screening Mammography (9204 images) and on the Portuguese INbreast dataset (410 images) with two different loss functions, binary cross-entropy loss with soft Jaccard loss and a loss function based on focal Tversky index.
The best models were trained on the Oulu Dataset of Screening Mammography with the focal Tversky loss. The best segmentation result achieved was a Dice similarity coefficient of 0.816 on correctly segmented masses and a classification accuracy of 88.7% on the INbreast dataset. On the Oulu Dataset of Screening Mammography, the best results were a Dice score of 0.763 and a classification accuracy of 83.3%. The results between the pretrained models were similar, and the pretrained models had better results than the non-pretrained models. In conclusion, deep transfer learning is very suitable for mammography mass segmentation and the choice of loss function had a large impact on the results.Rinnan massojen segmentointi mammografiakuvista syvÀ- ja siirto-oppimista hyödyntÀen. TiivistelmÀ. Mammografia on röntgenkuvantamismenetelmÀ, jota kÀytetÀÀn rintÀsyövÀn seulontaan. Mammografiakuvien seulonta on aikaa vievÀÀ ja niiden analysoimisen avuksi on kehitelty useita tietokoneavusteisia ratkaisuja. SyvÀoppimisella tarkoitetaan monikerroksisten neuroverkkojen kÀyttöÀ eri tehtÀvien ratkaisemiseen. SyvÀoppimismenetelmÀt ovat ajan myötÀ kehittyneet ja tulleet suosituiksi kuvien segmentoimiseen. Yksi tapa yhdistÀÀ syvÀ- ja siirtooppimista on hyödyntÀÀ neuroverkkoja esiopetettujen painojen kanssa, mikÀ auttaa parantamaan neuroverkkojen suorituskykyÀ.
TÀssÀ diplomityössÀ tutkittiin syvÀ- ja siirto-oppimisen kÀyttöÀ syöpÀisten massojen segmentoimiseen mammografiakuvista. KÀytetyt konvoluutioneuroverkot olivat esikoulutettuja ja hienosÀÀdettyjÀ. LisÀksi niillÀ oli enkooderi-dekooderi arkkitehtuuri. ResNet22 enkooderi oli esikoulutettu mammografia kuvilla, kun taas ResNet34 enkooderi oli esikoulutettu monenlaisilla vÀrikuvilla. NÀihin enkoodereihin yhdistettiin joko U-Net:n tai piirrepyramidiverkon dekooderi. LisÀksi kÀytettiin U-Net mallia ilman esikoulutusta. NÀmÀ viisi erilaista mallia koulutettiin ja testattiin sekÀ Oulun Mammografiaseulonta DatasetillÀ (9204 kuvaa) ettÀ portugalilaisella INbreast datasetillÀ (410 kuvaa) kÀyttÀen kahta eri tavoitefunktiota, jotka olivat binÀÀriristientropia yhdistettynÀ pehmeÀllÀ Jaccard-indeksillÀ ja fokaaliin Tversky indeksiin perustuva tavoitefunktiolla.
Parhaat mallit olivat koulutettu Oulun datasetillÀ fokaalilla Tversky tavoitefunktiolla. Parhaat tulokset olivat 0,816 Dice kerroin oikeissa positiivisissa segmentaatioissa ja 88,7 % luokittelutarkkuus INbreast datasetissÀ. Esikoulutetut mallit antoivat parempia tuloksia kuin mallit joita ei esikoulutettu. Oulun datasetillÀ parhaat tulokset olivat 0,763:n Dice kerroin ja 83,3 % luokittelutarkkuus. Tuloksissa ei ollut suurta eroa esikoulutettujen mallien vÀlillÀ. Tulosten perusteella syvÀ- ja siirto-oppiminen soveltuvat hyvin massojen segmentoimiseen mammografiakuvista. LisÀksi tavoitefunktiovalinnalla saatiin suuri vaikutus tuloksiin
Building body identities - exploring the world of female bodybuilders
This thesis explores how female bodybuilders seek to develop and maintain a viable sense of self despite being stigmatized by the gendered foundations of what Erving Goffman (1983) refers to as the 'interaction order'; the unavoidable presentational context in which identities are forged during the course of social life. Placed in the context of an overview of the historical treatment of women's bodies, and a concern with the development of bodybuilding as a specific form of body modification, the research draws upon a unique two year ethnographic study based in the South of England, complemented by interviews with twenty-six female bodybuilders, all of whom live in the U.K. By mapping these extraordinary women's lives, the research illuminates the pivotal spaces and essential lived experiences that make up the female bodybuilder. Whilst the women appear to be embarking on an 'empowering' radical body project for themselves, the consequences of their activity remains culturally ambivalent. This research exposes the 'Janus-faced' nature of female bodybuilding, exploring the ways in which the women negotiate, accommodate and resist pressures to engage in more orthodox and feminine activities and appearances
Image classification over unknown and anomalous domains
A longstanding goal in computer vision research is to develop methods that are simultaneously applicable to a broad range of prediction problems. In contrast to this, models often perform best when they are specialized to some task or data type. This thesis investigates the challenges of learning models that generalize well over multiple unknown or anomalous modes and domains in data, and presents new solutions for learning robustly in this setting.
Initial investigations focus on normalization for distributions that contain multiple sources (e.g. images in different styles like cartoons or photos). Experiments demonstrate the extent to which existing modules, batch normalization in particular, struggle with such heterogeneous data, and a new solution is proposed that can better handle data from multiple visual modes, using differing sample statistics for each.
While ideas to counter the overspecialization of models have been formulated in sub-disciplines of transfer learning, e.g. multi-domain and multi-task learning, these usually rely on the existence of meta information, such as task or domain labels. Relaxing this assumption gives rise to a new transfer learning setting, called latent domain learning in this thesis, in which training and inference are carried out over data from multiple visual domains, without domain-level annotations. Customized solutions are required for this, as the performance of standard models degrades: a new data augmentation technique that interpolates between latent domains in an unsupervised way is presented, alongside a dedicated module that sparsely accounts for hidden domains in data, without requiring domain labels to do so.
In addition, the thesis studies the problem of classifying previously unseen or anomalous modes in data, a fundamental problem in one-class learning, and anomaly detection in particular. While recent ideas have been focused on developing self-supervised solutions for the one-class setting, in this thesis new methods based on transfer learning are formulated. Extensive experimental evidence demonstrates that a transfer-based perspective benefits new problems that have recently been proposed in anomaly detection literature, in particular challenging semantic detection tasks
Supernatural crossing in Republican Chinese fiction, 1920sâ1940s
This dissertation studies supernatural narratives in Chinese fiction from the mid-1920s to the 1940s. The literary works present phenomena or elements that are or appear to be supernatural, many of which remain marginal or overlooked in Sinophone and Anglophone academia. These sources are situated in the May Fourth/New Culture ideological context, where supernatural narratives had to make way for the progressive intellectualsâ literary realism and their allegorical application of supernatural motifs. In the face of realism, supernatural narratives paled, dismissed as impractical fantasies that distract one from facing and tackling real life.
Nevertheless, I argue that the supernatural narratives do not probe into another mystical dimension that might co-exist alongside the empirical world. Rather, they imagine various cases of the charactersâ crossing to voice their discontent with contemporary society or to reflect on the notion of reality. âCrossingâ relates to charactersâ acts or processes of trespassing the boundary that separates the supernatural from the conventional natural world, thus entailing encounters and interaction between the natural and the supernatural. The dissertation examines how crossing, as a narrative device, disturbs accustomed and mundane situations, releases hidden tensions, and discloses repressed truths in Republican fiction.
There are five types of crossing in the supernatural narratives.
Type 1 is the crossing into âhauntedâ houses. This includes (intangible) human agency crossing into domestic spaces and revealing secrets and truths concealed by the scary, feigned âhauntingâ, thus exposing the hidden evil and the other house occupiersâ silenced, suffocated state.
Type 2 is men crossing into female ghostsâ apparitional residences. The female ghosts allude to heart-breaking, traumatic experiences in socio-historical reality, evoking sympathetic concern for suffering individuals who are caught in social upheavals.
Type 3 is the crossing from reality into the charactersâ delusional/hallucinatory realities. While they physically remain in the empirical world, the charactersâ abnormal perceptions lead them to exclusive, delirious, and quasi-supernatural experiences of reality. Their crossings blur the concrete boundaries between the real and the unreal on the mental level: their abnormal perceptions construct a significant, meaningful reality for them, which may be as real as the commonly regarded objective reality.
Type 4 is the crossing into the netherworld modelled on the real world in the authorsâ observation and bears a spectrum of satirised objects of the Republican society.
The last type is immortal visitors crossing into the human world. This type satirises humanityâs vices and destructive potential.
The primary sources demonstrate their writersâ witty passion to play with super--natural notions and imagery (such as ghosts, demons, and immortals) and stitch them into vivid, engaging scenes using techniques such as the gothic, the grotesque, and the satirical, in order to evoke sentiments such as terror, horror, disgust, dis--orientation, or awe, all in service of their insights into realist issues. The works also creatively tailor traditional Chinese modes and motifs, which exemplifies the revival of Republican interest in traditional cultural heritage. The supernatural narratives may amaze or disturb the reader at first, but what is more shocking, unpleasantly nudging, or thought-provoking is the problematic society and peopleâs lives that the supernatural (misunderstandings) eventually reveals. They present a more compre--hensive treatment of reality than Republican literature with its revolutionary consciousness surrounding class struggle. The critical perspectives of the supernatural narratives include domestic space, unacknowledged history and marginal individuals, abnormal mentality, and pervasive weaknesses in humanity.
The crossing and supernatural narratives function as a means of better understanding the lived reality.
This study gathers diverse primary sources written by Republican writers from various educational and political backgrounds and interprets them from a rare perspective, thus filling a research gap. It promotes a fuller view of supernatural narratives in twentieth-century Chinese literature. In terms of reflecting the social and personal reality of the Republican era, the supernatural narratives supplement the realist fiction of the time
Embodying entrepreneurship: everyday practices, processes and routines in a technology incubator
The growing interest in the processes and practices of entrepreneurship has
been dominated by a consideration of temporality. Through a thirty-six-month
ethnography of a technology incubator, this thesis contributes to extant
understanding by exploring the effect of space. The first paper explores how
class structures from the surrounding city have appropriated entrepreneurship
within the incubator. The second paper adopts a more explicitly spatial analysis
to reveal how the use of space influences a common understanding of
entrepreneurship. The final paper looks more closely at the entrepreneurs within
the incubator and how they use visual symbols to develop their identity. Taken
together, the three papers reject the notion of entrepreneurship as a primarily
economic endeavour as articulated through commonly understood language and
propose entrepreneuring as an enigmatic attractor that is accessed through the
ambiguity of the non-verbal to develop the ânewâ. The thesis therefore contributes
to the understanding of entrepreneurship and proposes a distinct role for the non-verbal in that understanding
Data-to-text generation with neural planning
In this thesis, we consider the task of data-to-text generation, which takes non-linguistic
structures as input and produces textual output. The inputs can take the form of
database tables, spreadsheets, charts, and so on. The main application of data-to-text
generation is to present information in a textual format which makes it accessible to
a layperson who may otherwise find it problematic to understand numerical figures.
The task can also automate routine document generation jobs, thus improving human
efficiency. We focus on generating long-form text, i.e., documents with multiple paragraphs. Recent approaches to data-to-text generation have adopted the very successful
encoder-decoder architecture or its variants. These models generate fluent (but often
imprecise) text and perform quite poorly at selecting appropriate content and ordering
it coherently. This thesis focuses on overcoming these issues by integrating content
planning with neural models. We hypothesize data-to-text generation will benefit from
explicit planning, which manifests itself in (a) micro planning, (b) latent entity planning, and (c) macro planning. Throughout this thesis, we assume the input to our
generator are tables (with records) in the sports domain. And the output are summaries
describing what happened in the game (e.g., who won/lost, ..., scored, etc.).
We first describe our work on integrating fine-grained or micro plans with data-to-text generation. As part of this, we generate a micro plan highlighting which records
should be mentioned and in which order, and then generate the document while taking
the micro plan into account.
We then show how data-to-text generation can benefit from higher level latent entity planning. Here, we make use of entity-specific representations which are dynam ically updated. The text is generated conditioned on entity representations and the
records corresponding to the entities by using hierarchical attention at each time step.
We then combine planning with the high level organization of entities, events, and
their interactions. Such coarse-grained macro plans are learnt from data and given
as input to the generator. Finally, we present work on making macro plans latent
while incrementally generating a document paragraph by paragraph. We infer latent
plans sequentially with a structured variational model while interleaving the steps of
planning and generation. Text is generated by conditioning on previous variational
decisions and previously generated text.
Overall our results show that planning makes data-to-text generation more interpretable, improves the factuality and coherence of the generated documents and re duces redundancy in the output document
TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH
Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on peopleâs lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)
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