14,991 research outputs found

    Serving to secure "Global Korea": Gender, mobility, and flight attendant labor migrants

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    This dissertation is an ethnography of mobility and modernity in contemporary South Korea (the Republic of Korea) following neoliberal restructuring precipitated by the Asian Financial Crisis (1997). It focuses on how comparative “service,” “security,” and “safety” fashioned “Global Korea”: an ongoing state-sponsored project aimed at promoting the economic, political, and cultural maturation of South Korea from a once notoriously inhospitable, “backward” country (hujin’guk) to a now welcoming, “advanced country” (sƏnjin’guk). Through physical embodiments of the culturally-specific idiom of “superior” service (sƏbisƭ), I argue that aspiring, current, and former Korean flight attendants have driven the production and maintenance of this national project. More broadly, as a driver of this national project, this occupation has emerged out of the country’s own aspirational flights from an earlier history of authoritarian rule, labor violence, and xenophobia. Against the backdrop of the Korean state’s aggressive neoliberal restructuring, globalization efforts, and current “Hell Chosun” (HelchosƏn) economy, a group of largely academically and/or class disadvantaged young women have been able secure individualized modes of pleasure, self-fulfillment, and class advancement via what I deem “service mobilities.” Service mobilities refers to the participation of mostly women in a traditionally devalued but growing sector of the global labor market, the “pink collar” economy centered around “feminine” care labor. Korean female flight attendants share labor skills resembling those of other foreign labor migrants (chiefly from the “Global South”), who perform care work deemed less desirable. Yet, Korean female flight attendants elude the stigmatizing, classed, and racialized category of “labor migrant.” Moreover, within the context of South Korea’s unique history of rapid modernization, the flight attendant occupation also commands considerable social prestige. Based on ethnographic and archival research on aspiring, current, and former Korean flight attendants, this dissertation asks how these unique care laborers negotiate a metaphorical and literal series of sustained border crossings and inspections between Korean flight attendants’ contingent status as lowly care-laboring migrants, on the one hand, and ostensibly glamorous, globetrotting elites, on the other. This study contends the following: first, the flight attendant occupation in South Korea represents new politics of pleasure and pain in contemporary East Asia. Second, Korean female flight attendants’ enactments of soft, sanitized, and glamorous (hwaryƏhada) service help to purify South Korea’s less savory past. In so doing, Korean flight attendants reconstitute the historical role of female laborers as burden bearers and caretakers of the Korean state.U of I OnlyAuthor submitted a 2-year U of I restriction extension request

    Grasping nothing: a study of minimal ontologies and the sense of music

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    If music were to have a proper sense – one in which it is truly given – one might reasonably place this in sound and aurality. I contend, however, that no such sense exists; rather, the sense of music takes place, and it does so with the impossible. To this end, this thesis – which is a work of philosophy and music – advances an ontology of the impossible (i.e., it thinks the being of what, properly speaking, can have no being) and considers its implications for music, articulating how ontological aporias – of the event, of thinking the absolute, and of sovereignty’s dismemberment – imply senses of music that are anterior to sound. John Cage’s Silent Prayer, a nonwork he never composed, compels a rerethinking of silence on the basis of its contradictory status of existence; Florian Hecker et al.’s Speculative Solution offers a basis for thinking absolute music anew to the precise extent that it is a discourse of meaninglessness; and Manfred Werder’s [yearn] pieces exhibit exemplarily that music’s sense depends on the possibility of its counterfeiting. Inso-much as these accounts produce musical senses that take the place of sound, they are also understood to be performances of these pieces. Here, then, thought is music’s organon and its instrument

    Data-to-text generation with neural planning

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    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

    Quantifying the Indirect Effect of Wolves on Aspen in Northern Yellowstone National Park: Evidence for a Trophic Cascade?

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    Yellowstone National Park is renowned for its incredible wildlife, and perhaps the most famous of these species is the gray wolf, which was reintroduced to the Park in the mid-1990s. After reintroduction, it was highly publicized by scientists, journalists, and environmentalists that the wolf both decreased elk density and changed elk behavior in a way that reduced elk effects on plants, a process known as a “trophic cascade.” Aspen, which is eaten by elk in winter, is one species at the forefront of Yellowstone trophic cascade research because it has been in decline across the Park for over a century. However, due to the challenges of measuring trophic cascades, there is continued uncertainty regarding the effects of wolves on aspen in northern Yellowstone. Thus, the purpose of my dissertation was to provide a comprehensive test of a trophic cascade in this system. Specifically, I used 20 years of data on aspen, elk, and wolves in Yellowstone to: 1) clarify annual trends in browsing and height of young aspen (a proxy for regeneration) after wolf reintroduction, 2) assess the influence of wolves scaring elk on aspen (“trait-mediated indirect effects”), and 3) evaluate the effect of wolves killing elk on aspen (“density-mediated indirect effects”). My research suggests that wolves indirectly contributed to increased aspen over story recruitment following their reintroduction by helping to reduce the elk population size, but elk response to the risk of wolf predation did not reduce elk foraging in a way that measurably increased aspen recruitment. Additionally, hunter harvest of elk north of the park was twice as important as wolf predation in causing increased aspen recruitment. However, despite wolves and hunters limiting elk abundance, it is still uncommon for young aspen to grow past peak browsing height (120-cm), indicating that many stands remain vulnerable to elk herbivory nearly 30 years after wolf reintroduction. These results highlight that the strength and mechanism of predator effects on plant communities are context-specific. Thus, using predator reintroduction as a tool for ecosystem restoration without considering the many factors that shape trophic cascades may result in different management and conservation outcomes than intended

    Photography and Aesthetics: a critical study on visual and textual narratives in the lifework of Sergio LarraĂ­n and its impact in 20th century Europe and Latin America

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    The main focus of this study is a theoretical exploration of critical approaches applicable to the work of the Chilean photographer Sergio LarraĂ­n (1931-2012). It presents analytical tools to contextualise and understand the importance and impact of his work in photographic studies and his portrayal of twentieth-century Latin American and European culture. It inspects in depth a large portion of his photo work, which is still only partially published and mostly reduced to his "active" period as a photojournalist, aside from the personal photographic exploration of his early and late career (C. Mena). This extended material creates a broader scope for understanding his photographs and him as a canonical photographer. This study analyses the photographer's trajectory as discourses of recollection of historical memory in time (Mauad) to trace LarraĂ­n's collective memory associated with his visual production. Such analysis helps decode his visual imagery and his projection and impact on the European and Latin American culture. This strategy helps solve a two fold problem: firstly, it generates an interpretive consistency to understand the Chilean's photographic practice; secondly, it explores the power of images as an aesthetic experience in the installation of nationalist ideologies and the creation of imaginaries (B. Anderson 163)

    A productive response to legacy system petrification

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    Requirements change. The requirements of a legacy information system change, often in unanticipated ways, and at a more rapid pace than the rate at which the information system itself can be evolved to support them. The capabilities of a legacy system progressively fall further and further behind their evolving requirements, in a degrading process termed petrification. As systems petrify, they deliver diminishing business value, hamper business effectiveness, and drain organisational resources. To address legacy systems, the first challenge is to understand how to shed their resistance to tracking requirements change. The second challenge is to ensure that a newly adaptable system never again petrifies into a change resistant legacy system. This thesis addresses both challenges. The approach outlined herein is underpinned by an agile migration process - termed Productive Migration - that homes in upon the specific causes of petrification within each particular legacy system and provides guidance upon how to address them. That guidance comes in part from a personalised catalogue of petrifying patterns, which capture recurring themes underlying petrification. These steer us to the problems actually present in a given legacy system, and lead us to suitable antidote productive patterns via which we can deal with those problems one by one. To prevent newly adaptable systems from again degrading into legacy systems, we appeal to a follow-on process, termed Productive Evolution, which embraces and keeps pace with change rather than resisting and falling behind it. Productive Evolution teaches us to be vigilant against signs of system petrification and helps us to nip them in the bud. The aim is to nurture systems that remain supportive of the business, that are adaptable in step with ongoing requirements change, and that continue to retain their value as significant business assets

    Deep Learning Language Models for music analysis and generation

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    [Abstract] In this project, we tackle the problem of predicting the next note in a monophonic musical piece. We choose a symbolic representation and extract it from digital sheet music. The problem is approached as four separate tasks, each of them corresponding to a specific property of the musical note. For each task, we compare the performance of both single and multi-output deep learning algorithms. Despite the severe class imbalance in our dataset, our models manage to generate balanced predictions for the four features.[Resumo] Neste proxecto tratamos o problema de predicir a seguinte nota nunha peza musical monofónica. Escollemos unha representación simbólica e extraémola dun conxunto de partituras dixitais. Afrontamos o problema como catro tarefas de predicción de propiedades inherentes å nota musical. Para cada tarefa, comparamos o rendemento de algoritmos de aprendizaxe profundo dunha e varias saídas. Aínda que o conxunto de datos estå moi descompensado, os nosos modelos son capaces de xerar predicións equilibradas nos catro problemas.Traballo fin de grao. Enxeñaría Informåtica. Curso 2021/202

    SYSTEMS METHODS FOR ANALYSIS OF HETEROGENEOUS GLIOBLASTOMA DATASETS TOWARDS ELUCIDATION OF INTER-TUMOURAL RESISTANCE PATHWAYS AND NEW THERAPEUTIC TARGETS

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    In this PhD thesis is described an endeavour to compile litterature about Glioblastoma key molecular mechanisms into a directed network followin Disease Maps standards, analyse its topology and compare results with quantitative analysis of multi-omics datasets in order to investigate Glioblastoma resistance mechanisms. The work also integrated implementation of Data Management good practices and procedures

    Graphical scaffolding for the learning of data wrangling APIs

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    In order for students across the sciences to avail themselves of modern data streams, they must first know how to wrangle data: how to reshape ill-organised, tabular data into another format, and how to do this programmatically, in languages such as Python and R. Despite the cross-departmental demand and the ubiquity of data wrangling in analytical workflows, the research on how to optimise the instruction of it has been minimal. Although data wrangling as a programming domain presents distinctive challenges - characterised by on-the-fly syntax lookup and code example integration - it also presents opportunities. One such opportunity is how tabular data structures are easily visualised. To leverage the inherent visualisability of data wrangling, this dissertation evaluates three types of graphics that could be employed as scaffolding for novices: subgoal graphics, thumbnail graphics, and parameter graphics. Using a specially built e-learning platform, this dissertation documents a multi-institutional, randomised, and controlled experiment that investigates the pedagogical effects of these. Our results indicate that the graphics are well-received, that subgoal graphics boost the completion rate, and that thumbnail graphics improve navigability within a command menu. We also obtained several non-significant results, and indications that parameter graphics are counter-productive. We will discuss these findings in the context of general scaffolding dilemmas, and how they fit into a wider research programme on data wrangling instruction
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