1,673 research outputs found
Researching animal research: What the humanities and social sciences can contribute to laboratory animal science and welfare
Every year around 80 million scientific procedures are carried out on animals globally. These experiments have the potential to generate new understandings of biology and clinical treatments. They also give rise to ongoing societal debate.This book demonstrates how the humanities and social sciences can contribute to understanding what is created through animal procedures - including constitutional forms of research governance, different institutional cultures of care, the professional careers of scientists and veterinarians, collaborations with patients and publics, and research animals, specially bred for experiments or surplus to requirements.Developing the idea of the animal research nexus, this book explores how connections and disconnections are made between these different elements, how these have reshaped each other historically, and how they configure the current practice and policy of UK animal research
Vision-enhanced Peg-in-Hole for automotive body parts using semantic image segmentation and object detection
Artificial Intelligence (AI) is an enabling technology in the context of Industry 4.0. In particular, the automotive sector is among those who can benefit most of the use of AI in conjunction with advanced vision techniques. The scope of this work is to integrate deep learning algorithms in an industrial scenario involving a robotic Peg-in-Hole task. More in detail, we focus on a scenario where a human operator manually positions a carbon fiber automotive part in the workspace of a 7 Degrees of Freedom (DOF) manipulator. To cope with the uncertainty on the relative position between the robot and the workpiece, we adopt a three stage strategy. The first stage concerns the Three-Dimensional (3D) reconstruction of the workpiece using a registration algorithm based on the Iterative Closest Point (ICP) paradigm. Such a procedure is integrated with a semantic image segmentation neural network, which is in charge of removing the background of the scene to improve the registration. The adoption of such network allows to reduce the registration time of about 28.8%. In the second stage, the reconstructed surface is compared with a Computer Aided Design (CAD) model of the workpiece to locate the holes and their axes. In this stage, the adoption of a Convolutional Neural Network (CNN) allows to improve the holes’ position estimation of about 57.3%. The third stage concerns the insertion of the peg by implementing a search phase to handle the remaining estimation errors. Also in this case, the use of the CNN reduces the search phase duration of about 71.3%. Quantitative experiments, including a comparison with a previous approach without both the segmentation network and the CNN, have been conducted in a realistic scenario. The results show the effectiveness of the proposed approach and how the integration of AI techniques improves the success rate from 84.5% to 99.0%
"It's not a career": Platform work among young people aged 16-19
In the online gig economy, or platform work as it is sometimes known, work can be organised through websites and smartphone apps. People can drive for Uber or Deliveroo, sell items on eBay or Etsy, or rent their properties on Airbnb.
This research examines the views of young people between the ages of 16 and 19 in the United Kingdom to see whether they knew about the online gig economy, whether they were using it already to earn money, and whether they expected to use it for their careers. It discovers careers professionals’ levels of knowledge, and their ability (and desire) to include the gig economy in their professional practice.
This research contributes to discussions about what constitutes decent work, and whether it can be found within the online gig economy. The results point to ways in which careers practice could include platform work as a means of extending young people’s knowledge about alternative forms of work. This study also makes a theoretical contribution to literature, bringing together elements of careership, cognitive schema theory, and motivational theory and psychology of working theory, in a novel combination, to explain how young people were thinking about platform work in the context of their careers
Comparing the production of a formula with the development of L2 competence
This pilot study investigates the production of a formula with the development of L2 competence over proficiency levels of a spoken learner corpus. The results show that the formula
in beginner production data is likely being recalled holistically from learners’ phonological
memory rather than generated online, identifiable by virtue of its fluent production in absence
of any other surface structure evidence of the formula’s syntactic properties. As learners’ L2
competence increases, the formula becomes sensitive to modifications which show structural
conformity at each proficiency level. The transparency between the formula’s modification
and learners’ corresponding L2 surface structure realisations suggest that it is the independent
development of L2 competence which integrates the formula into compositional language,
and ultimately drives the SLA process forward
Second-Person Surveillance: Politics of User Implication in Digital Documentaries
This dissertation analyzes digital documentaries that utilize second-person address and roleplay to make users feel implicated in contemporary refugee crises, mass incarceration in the U.S., and state and corporate surveillances. Digital documentaries are seemingly more interactive and participatory than linear film and video documentary as they are comprised of a variety of auditory, visual, and written media, utilize networked technologies, and turn the documentary audience into a documentary user. I draw on scholarship from documentary, game, new media, and surveillance studies to analyze how second-person address in digital documentaries is configured through user positioning and direct address within the works themselves, in how organizations and creators frame their productions, and in how users and players respond in reviews, discussion forums, and Let’s Plays. I build on Michael Rothberg’s theorization of the implicated subject to explore how these digital documentaries bring the user into complicated relationality with national and international crises. Visually and experientially implying that users bear responsibility to the subjects and subject matter, these works can, on the one hand, replicate modes of liberal empathy for suffering, distant “others” and, on the other, simulate one’s own surveillant modes of observation or behavior to mirror it back to users and open up one’s offline thoughts and actions as a site of critique.
This dissertation charts how second-person address shapes and limits the political potentialities of documentary projects and connects them to a lineage of direct address from educational and propaganda films, museum exhibits, and serious games. By centralizing the user’s individual experience, the interventions that second-person digital documentaries can make into social discourse change from public, institution-based education to more privatized forms of sentimental education geared toward personal edification and self-realization. Unless tied to larger initiatives or movements, I argue that digital documentaries reaffirm a neoliberal politics of individual self-regulation and governance instead of public education or collective, social intervention.
Chapter one focuses on 360-degree virtual reality (VR) documentaries that utilize the feeling of presence to position users as if among refugees and as witnesses to refugee experiences in camps outside of Europe and various dwellings in European cities. My analysis of Clouds Over Sidra (Gabo Arora and Chris Milk 2015) and The Displaced (Imraan Ismail and Ben C. Solomon 2015) shows how these VR documentaries utilize observational realism to make believable and immersive their representations of already empathetic refugees. The empathetic refugee is often young, vulnerable, depoliticized and dehistoricized and is a well-known trope in other forms of humanitarian media that continues into VR documentaries. Forced to Flee (Zahra Rasool 2017), I am Rohingya (Zahra Rasool 2017), So Leben Flüchtlinge in Berlin (Berliner Morgenpost 2017), and Limbo: A Virtual Experience of Waiting for Asylum (Shehani Fernando 2017) disrupt easy immersions into realistic-looking VR experiences of stereotyped representations and user identifications and, instead, can reflect back the user’s political inaction and surveillant modes of looking.
Chapter two analyzes web- and social media messenger-based documentaries that position users as outsiders to U.S. mass incarceration. Users are noir-style co-investigators into the crime of the prison-industrial complex in Fremont County, Colorado in Prison Valley: The Prison Industry (David Dufresne and Philippe Brault 2009) and co-riders on a bus transporting prison inmates’ loved ones for visitations to correctional facilities in Upstate New York in A Temporary Contact (Nirit Peled and Sara Kolster 2017). Both projects construct an experience of carceral constraint for users to reinscribe seeming “outside” places, people, and experiences as within the continuation of the racialized and classed politics of state control through mass incarceration. These projects utilize interfaces that create a tension between replicating an exploitative hierarchy between non-incarcerated users and those subject to mass incarceration while also de-immersing users in these experiences to mirror back the user’s supposed distance from this mode of state regulation.
Chapter three investigates a type of digital game I term dataveillance simulation games, which position users as surveillance agents in ambiguously dystopian nation-states and force users to use their own critical thinking and judgment to construct the criminality of state-sanctioned surveillance targets. Project Perfect Citizen (Bad Cop Studios 2016), Orwell: Keeping an Eye on You (Osmotic Studios 2016), and Papers, Please (Lucas Pope 2013) all create a dual empathy: players empathize with bureaucratic surveillance agents while empathizing with surveillance targets whose emails, text messages, documents, and social media profiles reveal them to be “normal” people. I argue that while these games show criminality to be a construct, they also utilize a racialized fear of the loss of one’s individual privacy to make players feel like they too could be surveillance targets.
Chapter four examines personalized digital documentaries that turn users and their data into the subject matter. Do Not Track (Brett Gaylor 2015), A Week with Wanda (Joe Derry Hall 2019), Stealing Ur Feelings (Noah Levenson 2019), Alfred Premium (Joël Ronez, Pierre Corbinais, and Émilie F. Grenier 2019), How They Watch You (Nick Briz 2021), and Fairly Intelligent™ (A.M. Darke 2021) track, monitor, and confront users with their own online behavior to reflect back a corporate surveillance that collects, analyzes, and exploits user data for profit. These digital documentaries utilize emotional fear- and humor-based appeals to persuade users that these technologies are controlling them, shaping their desires and needs, and dehumanizing them through algorithmic surveillance
Synthetic Aperture Radar (SAR) Meets Deep Learning
This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports
A review of technical factors to consider when designing neural networks for semantic segmentation of Earth Observation imagery
Semantic segmentation (classification) of Earth Observation imagery is a
crucial task in remote sensing. This paper presents a comprehensive review of
technical factors to consider when designing neural networks for this purpose.
The review focuses on Convolutional Neural Networks (CNNs), Recurrent Neural
Networks (RNNs), Generative Adversarial Networks (GANs), and transformer
models, discussing prominent design patterns for these ANN families and their
implications for semantic segmentation. Common pre-processing techniques for
ensuring optimal data preparation are also covered. These include methods for
image normalization and chipping, as well as strategies for addressing data
imbalance in training samples, and techniques for overcoming limited data,
including augmentation techniques, transfer learning, and domain adaptation. By
encompassing both the technical aspects of neural network design and the
data-related considerations, this review provides researchers and practitioners
with a comprehensive and up-to-date understanding of the factors involved in
designing effective neural networks for semantic segmentation of Earth
Observation imagery.Comment: 145 pages with 32 figure
Self-prior guided pixel adversarial networks for blind image inpainting
Blind image inpainting involves two critical aspects, i.e. "where to inpaint" and "how to inpaint". Knowing "where to inpaint" can eliminate the interference arising from corrupted pixel values; a good "how to inpaint" strategy yields high-quality inpainted results robust to various corruptions. In existing methods, these two aspects usually lack explicit and separate consideration. This paper fully explores these two aspects and proposes a self-prior guided inpainting network (SIN). The self-priors are obtained by detecting semantic-discontinuous regions and by predicting global semantic structures of the input image. On the one hand, the self-priors are incorporated into the SIN, which enables the SIN to perceive valid context information from uncorrupted regions and to synthesize semantic-aware textures for corrupted regions. On the other hand, the self-priors are reformulated to provide a pixel-wise adversarial feedback and a high-level semantic structure feedback, which can promote the semantic continuity of inpainted images. Experimental results demonstrate that our method achieves state-of-the-art perfomance in metric scores and in visual quality. It has an advantage over many existing methods that assume "where to inpaint" is known in advance. Extensive experiments on a series of related image restoration tasks validate the effectiveness of our method in obtaining high-quality inpainting
Musiktheorie als interdisziplinäres Fach: 8. Kongress der Gesellschaft für Musiktheorie Graz 2008
Im Oktober 2008 fand an der Universität für Musik und darstellende Kunst Graz (KUG) der 8. Kongress der Gesellschaft für Musiktheorie (GMTH) zum Thema »Musiktheorie als interdisziplinäres Fach« statt. Die hier vorgelegten gesammelten Beiträge akzentuieren Musiktheorie als multiperspektivische wissenschaftliche Disziplin in den Spannungsfeldern Theorie/Praxis, Kunst/Wissenschaft und Historik/Systematik. Die sechs Kapitel ergründen dabei die Grenzbereiche zur Musikgeschichte, Musikästhetik, zur Praxis musikalischer Interpretation, zur kompositorischen Praxis im 20. und 21. Jahrhundert, zur Ethnomusikologie sowie zur Systematischen Musikwissenschaft. Insgesamt 45 Aufsätze, davon 28 in deutscher, 17 in englischer Sprache, sowie die Dokumentation einer Podiumsdiskussion zeichnen in ihrer Gesamtheit einen höchst lebendigen und gegenwartsbezogenen Diskurs, der eine einzigartige Standortbestimmung des Fachs Musiktheorie bietet.The 8th congress of the Gesellschaft für Musiktheorie (GMTH) took place in October 2008 at the University for Music and Dramatic Arts Graz (KUG) on the topic »Music Theory and Interdisciplinarity«. The collected contributions characterize music theory as a multi-faceted scholarly discipline at the intersection of theory/practice, art/science and history/system. The six chapters explore commonalties with music history, music aesthetics, musical performance, compositional practice in twentieth- and twenty-first-century music, ethnomusicology and systematic musicology. A total of 45 essays (28 in German, 17 in English) and the documentation of a panel discussion form a vital discourse informed by contemporaneous issues of research in a broad number of fields, providing a unique overview of music theory today. A comprehensive English summary appears at the beginning of all contributions
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