1,440 research outputs found

    Digital Technologies for Teaching English as a Foreign/Second Language: a collective monograph

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    Колективна монографія розкриває різні аспекти використання цифрових технологій у навчанні англійської мови як іноземної/другої мови (цифровий сторітелінг, мобільні застосунки, інтерактивне навчання і онлайн-ігри, тощо) та надає освітянам і дослідникам ресурс для збагачення їхньої професійної діяльності. Окрема увага приділена цифровим інструментам для впровадження соціально-емоційного навчання та інклюзивної освіти на уроках англійської мови. Для вчителів англійської мови, методистів, викладачів вищих закладів освіти, науковців, здобувачів вищої освіти

    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

    The development, feasibility, and acceptability of a breakfast group intervention for stroke rehabilitation

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    Background: There are 1.2 million stroke survivors in the UK and the number is projected to increase significantly over the next decade. Research suggests that between 50% and 80% of hospitalised stroke survivors experience difficulties with eating and drinking. Presently, rehabilitation approaches to address these difficulties involve individual rehabilitation sessions led by uni-professionals. Recent national stroke guidance recommends that stroke survivors receive three hours of daily rehabilitation and emphasises the importance of addressing the psychosocial aspects of recovery. Implementing these recommendations presents a challenge to healthcare professionals, who must explore innovative methods to provide the necessary rehabilitation intensity. This study aimed to address these challenges by codesigning a multi-disciplinary breakfast group intervention and implementation toolkit to improve psychosocial outcomes. Methods: The Hawkins 3-step framework for intervention design was used to develop a multidisciplinary breakfast group intervention and to understand if it was acceptable and feasible for patients and healthcare professionals in an acute stroke ward. The Hawkins 3- steps were 1) evidence review and consultations 2) coproduction 3) prototyping. In collaboration with fifteen stakeholders, a prototype breakfast group intervention and implementation toolkit were codesigned over four months. Experience-based Codesign was used to engage stakeholders. Results: The literature review is the first to investigate the psychosocial impact of eating and drinking difficulties post stroke. The key finding was the presence of psychological and social impacts which included, the experience of loss, fear, embarrassment shame and humiliation as well as social isolation. Stroke survivors were striving to get back to normality and this included the desire to socially dine with others. Two prototype iterations of the intervention were tested with 16 stroke survivors across three hospital sites. The multidisciplinary breakfast group intervention was designed to offer intensive rehabilitation in a social group context. The codesigned implementation toolkit guided a personalised and tailored approach. A perceived benefit of the intervention was the opportunity to address the psychosocial aspects of eating and drinking rehabilitation as well as providing physical rehabilitation. Stroke survivors highly value the opportunity to socialise and receive support from their peers. The intervention was acceptable to both patients and healthcare professionals, and the workforce model proved practical and feasible to deliver using a collaborative approach in the context of resource-limited healthcare. Conclusions: The breakfast group interventions, developed through codesign, were positively received by patients and staff and feasible to deliver. They introduce an innovative and novel approach to stroke rehabilitation, personalised to each individual's needs, and offer a comprehensive intervention which addresses both physical and psychosocial aspects which target challenges related to eating and drinking. Unique contributions of this study include a theoretical model for breakfast group interventions, a programme theory and practical tool kit for clinicians to support the translation of research findings and implement breakfast groups in clinical practice

    Talking about personal recovery in bipolar disorder: Integrating health research, natural language processing, and corpus linguistics to analyse peer online support forum posts

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    Background: Personal recovery, ‘living a satisfying, hopeful and contributing lifeeven with the limitations caused by the illness’ (Anthony, 1993) is of particular value in bipolar disorder where symptoms often persist despite treatment. So far, personal recovery has only been studied in researcher-constructed environments (interviews, focus groups). Support forum posts can serve as a complementary naturalistic data source. Objective: The overarching aim of this thesis was to study personal recovery experiences that people living with bipolar disorder have shared in online support forums through integrating health research, NLP, and corpus linguistics in a mixed methods approach within a pragmatic research paradigm, while considering ethical issues and involving people with lived experience. Methods: This mixed-methods study analysed: 1) previous qualitative evidence on personal recovery in bipolar disorder from interviews and focus groups 2) who self-reports a bipolar disorder diagnosis on the online discussion platform Reddit 3) the relationship of mood and posting in mental health-specific Reddit forums (subreddits) 4) discussions of personal recovery in bipolar disorder subreddits. Results: A systematic review of qualitative evidence resulted in the first framework for personal recovery in bipolar disorder, POETIC (Purpose & meaning, Optimism & hope, Empowerment, Tensions, Identity, Connectedness). Mainly young or middle-aged US-based adults self-report a bipolar disorder diagnosis on Reddit. Of these, those experiencing more intense emotions appear to be more likely to post in mental health support subreddits. Their personal recovery-related discussions in bipolar disorder subreddits primarily focussed on three domains: Purpose & meaning (particularly reproductive decisions, work), Connectedness (romantic relationships, social support), Empowerment (self-management, personal responsibility). Support forum data highlighted personal recovery issues that exclusively or more frequently came up online compared to previous evidence from interviews and focus groups. Conclusion: This project is the first to analyse non-reactive data on personal recovery in bipolar disorder. Indicating the key areas that people focus on in personal recovery when posting freely and the language they use provides a helpful starting point for formal and informal carers to understand the concerns of people diagnosed with bipolar disorder and to consider how best to offer support

    Re-envisioning access for the digital preservation community: challenges, opportunities and recommendations

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    Digital material is not new and has been preserved for a couple of decades now. With a growing digital preservation community, and a growing number of practitioners identifying as doing something digital, there is an understanding that this material is here to stay. More and more institutions are publishing digital strategies or creating networks focusing on digital material. However, when looking at this in practice there seems to be a disconnect between what is being stated within these networks and strategies and what is being made accessible to the public. This thesis will explore this disconnect by first understanding how the digital preservation community has been providing access to this material and how they are envisioning it in the future. This exploration surfaces both a) how digital material can no longer be seen as separate from the infrastructure that ensures its materiality and b) how the provision of access is not just a technological question, but also a social, legal and ethical one. This thesis will also seek to explore the ways in which those who identify as digital preservation practitioners articulate their role and responsibilities. It will do so by drawing on relevant literature and gaining perspectives from practitioners and other relevant participants through in-depth interviews. Building from this exploration, this thesis will offer recommendations for how this practice can move forward in negotiating the provision of access to digital material in the online public space of the internet. This research is part of a collaborative project with The National Archives, UK where a number of the ideas encountered during this work were explored in practice. Some of these results have helped shape the recommendations given in the final chapters of this thesis

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil

    Northeastern Illinois University, Academic Catalog 2023-2024

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    https://neiudc.neiu.edu/catalogs/1064/thumbnail.jp

    Learning from Audio, Vision and Language Modalities for Affect Recognition Tasks

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    The world around us as well as our responses to worldly events are multimodal in nature. For intelligent machines to integrate seamlessly into our world, it is imperative that they can process and derive useful information from multimodal signals. Such capabilities can be provided to machines by employing multimodal learning algorithms that consider both the individual characteristics of unimodal signals as well as the complementariness provided by multimodal signals. Based on the number of modalities available during the training and testing phases, learning algorithms can be of three categories: unimodal trained and unimodal tested, multimodal trained and multimodal tested, and multimodal trained and unimodal tested algorithms. This thesis provides three contributions, one for each category and focuses on three modalities that are important for human-human and human-machine communication, namely, audio (paralinguistic speech), vision (facial expressions) and language (linguistic speech) signals. For several applications, either due to hardware limitations or deployment specifications, unimodal trained and tested systems suffice. Our first contribution, for the unimodal trained and unimodal tested category, is an end-to-end deep neural network that uses raw speech signals as input for a computational paralinguistic task, namely, verbal conflict intensity estimation. Our model, which uses a convolutional recurrent architecture equipped with attention mechanism to focus on task-relevant instances of the input speech signal, eliminates the need for task-specific meta data or domain knowledge based manual refinement of hand-crafted generic features. The second contribution, for the multimodal trained and multimodal tested category, is a multimodal fusion framework that exploits both cross (inter) and intra-modal interactions for categorical emotion recognition from audiovisual clips. We explore the effectiveness of two types of attention mechanisms, namely, intra and cross-modal attention by creating two versions of our fusion framework. In many applications, multimodal signals might be available during model training phase, yet we cannot expect the availability of all modality signals during testing phase. Our third contribution addresses this situation wherein we propose a framework for cross-modal learning where paired audio-visual instances are used during training to develop test-time stand-alone unimodal models
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