5,637 research outputs found

    Southern Adventist University Undergraduate Catalog 2023-2024

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    Southern Adventist University\u27s undergraduate catalog for the academic year 2023-2024.https://knowledge.e.southern.edu/undergrad_catalog/1123/thumbnail.jp

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Graduate Catalog of Studies, 2023-2024

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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

    Soundscape in Urban Forests

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    This Special Issue of Forests explores the role of soundscapes in urban forested areas. It is comprised of 11 papers involving soundscape studies conducted in urban forests from Asia and Africa. This collection contains six research fields: (1) the ecological patterns and processes of forest soundscapes; (2) the boundary effects and perceptual topology; (3) natural soundscapes and human health; (4) the experience of multi-sensory interactions; (5) environmental behavior and cognitive disposition; and (6) soundscape resource management in forests

    Perceptions and Practicalities for Private Machine Learning

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    data they and their partners hold while maintaining data subjects' privacy. In this thesis I show that private computation, such as private machine learning, can increase end-users' acceptance of data sharing practices, but not unconditionally. There are many factors that influence end-users' privacy perceptions in this space; including the number of organizations involved and the reciprocity of any data sharing practices. End-users emphasized the importance of detailing the purpose of a computation and clarifying that inputs to private computation are not shared across organizations. End-users also struggled with the notion of protections not being guaranteed 100\%, such as in statistical based schemes, thus demonstrating a need for a thorough understanding of the risk form attacks in such applications. When training a machine learning model on private data, it is critical to understand the conditions under which that data can be protected; and when it cannot. For instance, membership inference attacks aim to violate privacy protections by determining whether specific data was used to train a particular machine learning model. Further, the successful transition of private machine learning theoretical research to practical use must account for gaps in achieving these properties that arise due to the realities of concrete implementations, threat models, and use cases; which is not currently the case

    Taylor University Catalog 2023-2024

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    The 2023-2024 academic catalog of Taylor University in Upland, Indiana.https://pillars.taylor.edu/catalogs/1128/thumbnail.jp

    Learning from Patterns : Information Retrieval and Visualisation Issues Between Bioimage Informatics and Digital Humanities

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    The large amount of data generated in different fields, among which bioimage informatics and digital humanities, is increasingly requiring appropriate automatic processing techniques, such as computer vision, data mining and particular visualisation tools, to extract information out of complexity and to clearly display it. This has led, in digital humanities, to the use of pattern recognition techniques similar to those applied in biology, chemistry and medical studies, but where patterns to be analysed and segmented are extracted from texts, images, audiovisual and online media rather than from cells and tissues. Regularities can be recognised through machine learning, based on artificial neural networks that are modelled, to some extent, after the brain's structure, showing a variety of analogies between natural and artificial world. These processes can also add information to 3D models for cultural heritage: data mining technologies allow information retrieval from archives and repositories, as well as the comparison of data in order to better understand the context of-and relationships between-works of art, thus producing knowledge enhancement. Various tools to describe complexity are here analysed not only for their educational aim, but also for their heuristic value, allowing new discoveries and connections between different disciplines
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