2,016 research outputs found

    Making the third mission possible: investigating academic staff experiences of community-engaged learning

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    Community-engaged Learning (CEL) is an intentional and structured pedagogical approach, which links learning objectives with community needs. Most of the existing literature is centred on Service-learning practice in the United States. To date, there have been no in-depth studies on the experiences and perspectives of practitioners who engage with CEL in a UK or more specifically, a Scottish Higher Education context. The thesis presents data collected from a qualitative study utilising documentary analysis of government and institutional literature and 23 in-depth interviews with University practitioners, managers and leaders. I explored factors which influence the perspectives and experiences of CEL practitioners at one Scottish, research-intensive Russell Group university. Adopting a research ontology informed by Margaret Archer’s Morphogenetic, Critical Realist approach, I analyse the data collected through the lens of an emancipatory Neo-Aristotelian virtue-ethics framework and argue that CEL practice at this university contributes to, what the evidence suggests is, its ultimate purpose: promoting and cultivating individual flourishing and emancipatory critical thinking for the common good. Focussing on university-community engagement, the findings suggest that there are some inconsistencies between how the University is portrayed in public-facing literature compared to the level of institutional support individual practitioners of CEL report receiving. I conclude that failure to adequately support CEL activity in the future could negatively impact the sustainability and quality of community engagement at Alba University

    RLS-LCD : an efficient Loop Closure Detection for Rotary-LiDAR Scans

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    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Provincialising whiteness: Òyìnbó and the politics of race in Lagos, Nigeria

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    Much academic work on racialisation processes to date has focused on a geographically restricted range of racial regimes characterised by white supremacy. This study broadens the geographical scope of analyses by looking at race-making practices in Lagos, Nigeria. I explore the geographical specificity of race-making in Lagos through interrogation of the concept of òyìnbó – a Yorùbá word most often translated into English as ‘white person.’ By highlighting the particular meanings attached to òyìnbó, and the political work that racialisation does in this understudied context, I argue for the need to provincialise understandings of whiteness in studies of global race-making processes. The project is based upon eleven months of ethnographic fieldwork with Lagosians of different generations and social demographics at three different research sites: a senior secondary school, the University of Lagos, and at a church. My findings suggest that divergent meanings are attached to òyìnbós in these contexts, which do not universally celebrate whiteness. Rather, the practice of race-making in Lagos predominantly addresses local political concerns, and common attributes associated with òyìnbós are primarily evaluated according to local people’s own moral economy. This results in highly ambivalent attitudes to òyìnbós as individuals and to òyìnbó as trope. I suggest that these attitudes can best be explained by situating constructions of òyìnbós within their wider social context in Lagos. By centring local understandings in this way, I argue that the political practice of race-making in Lagos is not purely a reflection of a singular, global racial hierarchy, but a means of actively engaging with global and local power structures. I propose that seeking to understand the emic nature of divergent global race-making processes in this way has the potential to broaden academic understanding of these and related social phenomena

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    A Critical Discourse Analysis Of Hbcus And Their Place In Science And Technology From 1979-80 As Told By Four National Newspapers

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    This study was an investigation of how national newspapers contributed to the reproduction of racism as they reported on Historically Black Colleges and Universities (HBCUs) and the need for more Black Americans in STEM programs. The existence of racism in newspaper discourse reaffirms the long-standing perception that HBCUs, and the Black Americans they serve, do not deserve full educational participation in society. The lack of diversity in STEM fields represents a key area where a critical exploration of how HBCUs are described is needed. Specifically, four national newspapers, the Los Angeles Times, the New York Times, the Wall Street Journal, and the Washington Post, printed during the period of March 7, 1979, to December 12, 1980 were explored. Critical race theory provided the theoretical foundation of the study to explain why racism is a continued aspect of society that limits the STEM access of HBCUs. The research question for the study sought to understand the constructed images of HBCUs and Black students present in national newspaper discourse with respect to STEM topics. Using a critical discourse analysis approach, the study included 15 articles relevant to the topic. A key marker of relevant discourse was the passing of the 1980 National Science Foundation Authorization and Science and Technology Equal Opportunities Act, which provided HBCU students with additional access to science and technology curriculums and degrees. The study found discourse that represented a battle for HBCU continued existence, images of Black students as academically incapable, and implicit uses of racism to uphold notions of White supremacy. Implications to the field include a need for a more critical lens to be taken when framing events about HBCUs and Black students as these contribute to the collective perception of these groups as inferior

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    An American Knightmare: Joker, Fandom, and Malicious Movie Meaning-Making

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    This monograph concerns the long-standing communication problem of how individuals can identify and resist the influence of unethical public speakers. Scholarship on the issue of what Socrates & Plato called the “Evil Lover” – i.e., the ill-intended rhetor – began with the Greek philosophers, but has carried into [post]Modern anxieties. For instance, the study of Nazi propaganda machines, and the rhetoric of Hitler himself, rejuvenated interest in the study of speech and communication in the U.S. and Europe. Whereas unscrupulous sophists used lectures and legal forums, and Hitler used a microphone, contemporary Evil Lovers primarily draw on new, internet-related tools to share their malicious influence. These new tools of influence are both more far-reaching and more subtle than the traditional practices of listening to a designated speaker appearing at an overtly political event. Rhetorician Ashley Hinck has recently noted the ways that popular culture – communication about texts which are commonly accessible and shared – are now significant sites through which citizens learn moral and political values. Accordingly, the talk of internet influencers who interpret popular texts for other fans has the potential to constitute strong persuasive power regarding ethics and civic responsibility. The present work identifies and responds to a particular case example of popular culture text that has been recently, and frequently, leveraged in moral and civic discourses: Todd Phillips’ Joker. Specifically, this study takes a hermeneutic approach to understanding responses, especially those explicitly invoking political ideology, to Joker as a method of examining civic meaning-making. A special emphasis is placed on the online film criticisms of Joker from white nationalist movie fans, who clearly exemplify ways that media responses can be leveraged by unethical speakers (i.e., Evil Lovers) and subtly diffused. The study conveys that these racist movie fans can embed values related to “trolling,” incelism, and xenophobia into otherwise seemingly innocuous talk about film. While the sharing of such speech does not immediately mean its positive reception, this kind of communication yet constitutes a new and understudied attack on democratic values such as justice and equity. The case of white nationalist movie fan film criticism therefore reflects a particular brand of communicative strategy for contemporary Evil Lovers in communicating unethical messages under the covert guise of mundane movie talk

    Synthetic Aperture Radar (SAR) Meets Deep Learning

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    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
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