91 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Towards Privacy Preservation of Federated Learning in Artificial Intelligence of Things

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    Under the need of processing huge amounts of data, providing high-quality service, and protecting user privacy in Artificial Intelligence of Things (AIoT), Federated Learning (FL) has been adopted as a promising technique to facilitate its broad applications. Although the importance of developing privacy-preserving FL has attracted lots of attention in different aspects, the existing research is still far from perfect in real applications. In this dissertation, we propose three privacy-related research accordingly towards three realistic weaknesses of federated learning in the AIoT scenarios, which solve the problems of private data inference, private data generation, and private data deletion in different stages of data life. First, to solve the privacy inference problem of traditional FL, we design a dual differentially private FL mechanism to achieve privacy preservation efficiently for both server side and local clients. In particular, our proposed method focuses on FL with non-independent identically distributed (non-i.i.d.) data distribution and gives theoretical analysis on privacy leakage as well as algorithm convergence. The second problem is to generate heterogeneous data privately in FL. To handle this challenging problem, we design a distributed generative model framework that can learn a powerful generator in hierarchical AIoT systems. Thirdly, we investigate a newly emerged machine unlearning problem, which is to remove a data point and its influence from the trained machine learning model with efficiency and effectiveness. Moreover, as the very first work on exact federated machine unlearning in literature, we design a quantization based method, which can remove unlearned data from multiple clients with significantly higher speed-up. All of the proposed methods are evaluated on different datasets, and the results output by our models express superiority over existing baselines

    Twin Research for Everyone. From Biology to Health, Epigenetics, and Psychology

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    The Proceedings of the 23rd Annual International Conference on Digital Government Research (DGO2022) Intelligent Technologies, Governments and Citizens June 15-17, 2022

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    The 23rd Annual International Conference on Digital Government Research theme is “Intelligent Technologies, Governments and Citizens”. Data and computational algorithms make systems smarter, but should result in smarter government and citizens. Intelligence and smartness affect all kinds of public values - such as fairness, inclusion, equity, transparency, privacy, security, trust, etc., and is not well-understood. These technologies provide immense opportunities and should be used in the light of public values. Society and technology co-evolve and we are looking for new ways to balance between them. Specifically, the conference aims to advance research and practice in this field. The keynotes, presentations, posters and workshops show that the conference theme is very well-chosen and more actual than ever. The challenges posed by new technology have underscored the need to grasp the potential. Digital government brings into focus the realization of public values to improve our society at all levels of government. The conference again shows the importance of the digital government society, which brings together scholars in this field. Dg.o 2022 is fully online and enables to connect to scholars and practitioners around the globe and facilitate global conversations and exchanges via the use of digital technologies. This conference is primarily a live conference for full engagement, keynotes, presentations of research papers, workshops, panels and posters and provides engaging exchange throughout the entire duration of the conference

    School Achievement and Failure: Prevention and Intervention Strategies.

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    School achievement and failure seem to be the result of multiple social, political and individual factors. The origins of school failure are complex and are not limited to school, because family and community risk factors can foster or inhibit the individual’s cognitive, social and emotional development. The content of this book reflects the state of the art in the research on school achievement and failure in Europe, Asia, North and South America.Frontiers Media S

    Exploring perspectives of people with type-1 diabetes on goalsetting strategies within self-management education and care

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    Background. Collaborative goal-setting strategies are widely recommended for diabetes self-management support within healthcare systems. Creating self-management plans that fit with peoples’ own goals and priorities has been linked with better diabetic control. Consequently, goal-setting has become a core component of many diabetes selfmanagement programmes such as the ‘Dose Adjustment for Normal Eating (DAFNE) programme’. Within DAFNE, people with Type-1 Diabetes (T1D) develop their own goals along with action-plans to stimulate goal-achievement. While widely implemented, limited research has explored how goal-setting strategies are experienced by people with diabetes.Therefore, this study aims to explore the perspectives of people with T1D on theimplementation and value of goal-setting strategies within DAFNE and follow-up diabetes care. Furthermore, views on barriers and facilitators to goal-attainment are explored.Methods. Semi-structured interviews were conducted with 20 people with T1D who attended a DAFNE-programme. Following a longitudinal qualitative research design, interviews took place 1 week, and 6-8 months after completion of DAFNE. A recurrent cross-sectional approach is applied in which themes will be identified at each time-point using thematic analyses.Expected results. Preliminary identified themes surround the difference in value that participants place on goal-setting strategies, and the lack of support for goal-achievement within diabetes care.Current stage. Data collection complete; data-analysis ongoing.Discussion. Goal-setting strategies are increasingly included in guidelines for diabetes support and have become essential parts of many primary care improvement schemes. Therefore, exploring the perspectives of people with T1D on the value and implementation of goal-setting strategies is vital for their optimal application
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