Results 61 to 70 of about 4,684 (203)

FL-MEC - predicting network traffic on edge with federated learning

Computer Science
Nowadays, two technological trends, Federated Learning (FL) and Edge Computing (EC), are becoming more and more important and influential. FL is a distributed machine learning strategy that allows learning on distributed data. It primarily allows performing learning operations close to the user, where we can gather data.
Marek Konieczny, Slawomir Zielinski, Patryk Paszko   +2 more
openaire   +1 more source

Clinical Outcomes of a Digital Companion in Periodontal Care: A Randomised Controlled Trial

Journal of Clinical Periodontology, EarlyView.
ABSTRACT Aim To evaluate the efficacy of a digital health companion app as an adjunct to systematic periodontal therapy. Methods Seven German university dental centres conducted this multi‐centre randomised controlled trial. Adults with periodontitis (n = 194) were assigned to standard periodontal care with or without the Paro‐ComPas app.
Bettina Dannewitz, James Deschner, Christof Dörfer, Henrik Dommisch, Peter Eickholz, Lukas Förster, Lukasz Jablonowski, Neelam Lingwal, Stefan Listl, Maurice Rütters, Lina Weinert, Nihad El Sayed, the Paro‐ComPas Collaborators, Philipp Bani, Valentin Bartha, Thomas Beikler, Pablo Cores Ziskoven, Miriam Cyris, Ivana Elez, Maurice Fahn, Jens Göbel, Jana Gortschakow, Christian Graetz, Ahmad Haseeb, Oliver Heinze, Laurenz Hermans, Daniela Hoedke, Maren Kahl, Ti‐Sun Kim, Julian Kohlmüller, Denica Kuzmanova, Yola Meisel, Tugay Nebilir, Antares Outatzis, Gerd Schneider, Mario Schröder, Alexander Spies, Ingvi Spies, Claudia Springer, Leonie Staffeldt, Jessica Vasseur, Patrizia Winkler   +41 more
wiley   +1 more source

A Framework for Sales Tax Base Expansion: Food Taxation in North Carolina and Applications for Other States

Public Budgeting &Finance, EarlyView.
Abstract The review of sales tax exemptions represents a significant undertaking for states across the United States. This analysis introduces a set of tax policy criteria to evaluate these exemptions in response to prevalent stakeholder considerations. We implement these criteria in the context of North Carolina's exemption of unprepared food from the
Whitney Afonso, Alex Combs
wiley   +1 more source

Adaptive Synchronistic Federated Learning: Balancing Communication Efficiency and Robustness in Heterogeneous Systems

IEEE Access
The rapid and widespread adoption of smartphones and IoT devices has led to massive volumes of decentralized data residing on edge devices. While this offers significant potential for machine learning applications, privacy regulations increasingly limit ...
Babak Esmaeili, Zahra Derakhshandeh
doaj   +1 more source

EneA-FL: Energy-aware orchestration for serverless federated learning

Future Generation Computer Systems
Federated Learning (FL) represents the de-facto standard paradigm for enabling distributed learning over multiple clients in real-world scenarios. Despite the great strides reached in terms of accuracy and privacy awareness, the real adoption of FL in real-world scenarios, in particular in industrial deployment environments, is still an open thread ...
Andrea Agiollo, Paolo Bellavista, Matteo Mendula, Andrea Omicini   +3 more
openaire   +2 more sources

Mitochondrial Ca2+ uniporter haploinsufficiency leads to sexually dimorphic redox imbalance and metabolic remodelling in the mouse brain

The Journal of Physiology, EarlyView.
Abstract figure legend The genetic inactivation of one Mcu allele leads to sex‐specific changes in neuronal function in adult mice, that is, the firing of action potentials and the relationship between cytosolic and mitochondrial Ca2+ levels. The ability to produce NAD(P)H by stimulated neural tissue is largely preserved in male mice but delayed in ...
Jenna Gray, Girish Halemirle, Beatriz Ferrán, Hadyn Rose, Traci L. Redwine, Sophia Pham, Bo Hagy, Atul Pranay, Jennifer Giorgione, Stacy A. Hussong, Veronica Galvan, Kenneth Humphries, Holly Van Remmen, Mike Kinter, William E. Sonntag, Pankaj K. Singh, Carlos Manlio Díaz‐García   +16 more
wiley   +1 more source

Recognizing Our Role in Reframing Disaster and Emergency Management Terminology to Enhance Human Agency and Responsibility

Perspectives of Earth and Space Scientists, Volume 7, Issue 1, December 2026.
Abstract This work addresses the critical issue of science literacy and science communication for scientists, researchers, officials, organizations, and the general public. Effective communication and trust between these groups are essential, particularly as the severity and scope of disasters continue to increase.
J. M. Trivedi, P. R. Buchanan, K. N. Owusu‐Daaku   +2 more
wiley   +1 more source

Assessing the Feasibility of Wearable Devices for Physiological Monitoring and Heat Risk Prediction in Outdoor Agricultural Workers

American Journal of Industrial Medicine, Volume 69, Issue 9, Page 722-744, September 2026.
ABSTRACT Background Outdoor agricultural workers experience significant heat exposure, yet few studies have evaluated whether wearable sensors can reliably measure continuous physiological responses in real field conditions. This pilot study examined the feasibility and predictive utility of core temperature, hydration, heart rate, and movement data ...
Sinan Sousan, Elizabeth Mizelle, Qiang Wu, Rui Wu, Guy Iverson, Ciprian Popoviciu, Dylan Hemedinger, Eliezer Loyola, Takari Hood, Monica Ramirez, Jo Anne Balanay   +10 more
wiley   +1 more source

Flexible and scalable federated learning with deep feature prompts for digital pathology

npj Digital Medicine
Collaborative learning across medical institutions is essential for building robust and generalisable digital pathology models. Federated learning (FL) enables collaboration without centralising data, yet its adoption is limited by high communication ...
Cong Cong, Yang Song, Antonio Di Ieva, Angela Chou, Anthony J. Gill, Enrico Coiera, Sidong Liu   +6 more
doaj   +1 more source

A personalized federated learning method based on the residual multi-head attention mechanism

Journal of King Saud University: Computer and Information Sciences
Federated Learning (FL) is a distributed machine learning technique for training machine learning models across multiple clients collaboratively. It allows multiple local devices to cooperatively train global models without compromising data privacy or ...
Zhaobin Li, Zixuan Zhong, Peiliang Zuo, Hong Zhao   +3 more
doaj   +1 more source