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Published in 2017 at "Personal and Ubiquitous Computing"
DOI: 10.1007/s00779-017-1016-2
Abstract: Television viewers interacting with second screens has become a common sight in the modern living room. Such activities are a mixture of related, semi-related, and non-related browsing of content. This growing trend is revolutionising the…
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Keywords:
device media;
television;
cross device;
multi device ... See more keywords
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Published in 2025 at "Analytical Chemistry"
DOI: 10.1021/acs.analchem.5c00185
Abstract: This paper presents a solution to the challenge of cross-device model generalization in blood-based infrared spectroscopy. As infrared spectroscopy becomes increasingly popular for analyzing human blood, ensuring that machine learning models trained on one device…
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Keywords:
spectroscopy;
infrared spectroscopy;
device;
cross device ... See more keywords
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Published in 2024 at "Nuclear Fusion"
DOI: 10.1088/1741-4326/ad3fca
Abstract: Abnormal (deviating from the target) variations in the plasma vertical position Z and current Ip (such as vertical displacements, transient Ip ‘spikes’ and quenches) constitute common elements of a disruption, a phenomenon that is to…
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Keywords:
plasma vertical;
vertical position;
device;
cross device ... See more keywords
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Published in 2024 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3417003
Abstract: While cross-device federated learning (FL) offers a privacy-preserving data processing approach for Internet of Things (IoT) devices, it introduces fresh privacy risks and elevated computational expenses. Current solutions prioritize data privacy, often overlooking identity privacy…
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Keywords:
cross device;
robust incentive;
privacy;
unlinkable anonymity ... See more keywords
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Published in 2022 at "IEEE Wireless Communications"
DOI: 10.1109/mwc.005.2100435
Abstract: The concept of federated learning (FL) was first proposed by Google in 2016. Since then, FL has been widely studied for the feasibility of application in various fields due to its potential to make full…
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Keywords:
cross device;
federated learning;
mobile devices;
framework ... See more keywords
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Published in 2024 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2024.3380669
Abstract: In cross-device federated learning, verifiable secure aggregation enables clients to aggregate their locally trained model parameters through a malicious server to obtain a global model. To prevent the malicious server from tampering with the results,…
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Keywords:
verifiable aggregation;
non interactive;
cross device;
federated learning ... See more keywords
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Published in 2024 at "IEEE Transactions on Mobile Computing"
DOI: 10.1109/tmc.2024.3450577
Abstract: The prevalence of cross-device resource sharing enables users to utilize various device resources of the connected mobile devices seamlessly. Since there are often numerous connected mobile devices under the same network, cross-device tasks are often…
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Keywords:
multi task;
device;
cross device;
resource sharing ... See more keywords
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Published in 2022 at "Proceedings of the ACM on Human-Computer Interaction"
DOI: 10.1145/3555192
Abstract: When working together, people frequently share information with each other to enable division of labour, assistance, and delegation of responsibility. The literature has explored both synchronous and asynchronous transfer techniques, known as Handoff and Deposit,…
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Keywords:
cross device;
handoff deposit;
transfer;
device transfer ... See more keywords
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3
Published in 2023 at "Journal of Librarianship and Information Science"
DOI: 10.1177/09610006221090956
Abstract: Users’ search performance indicates the effectiveness and success with which users’ information needs are met, which is calculated based on the relevance judgment by users themselves. This study proposed to explore the prediction of users’…
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Keywords:
cross device;
users search;
device search;
search performance ... See more keywords