Results 191 to 200 of about 36,405 (319)
This Perspective examines practical power solutions for wearable healthcare systems, highlighting the limits of standard batteries. It categorizes wearables into four domains—point‐of‐care diagnostics, episodic monitoring, continuous long‐term monitoring, and therapeutic platforms—and analyzes their power needs.
Seokheun Choi
wiley +1 more source
Adaptive Reinforcement Learning-Based Framework for Energy-Efficient Task Offloading in a Fog-Cloud Environment. [PDF]
Mikavica B, Kostic-Ljubisavljevic A.
europepmc +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
A direction aware predictive offloading framework for energy conscious mobile augmented reality systems. [PDF]
Jebamani SA, Sathianesan GW.
europepmc +1 more source
Conversing with machines: How AI is changing the way scientists think
Quantitative Biology, Volume 14, Issue 2, June 2026.
Anna Viktorovna Gavrilova, Carlo Galli
wiley +1 more source
ABSTRACT Amniotic fluid embolism (AFE) is a devastating and unpredictable obstetric emergency typically characterized by sudden cardiopulmonary collapse and coagulopathy during or shortly after delivery. It is triggered by an anaphylactoid‐histamine‐mediated systemic response, evidently with no available confirmatory tests in living patients.
Aniceth Muchunguzi +4 more
wiley +1 more source
Data quality-aware task offloading in Mobile Edge Computing: An Optimal Stopping Theory approach
Ibrahim Alghamdi +2 more
openalex +1 more source
UAV-Enabled Mobile Edge Computing: Offloading Optimization and Trajectory Design [PDF]
Fuhui Zhou +3 more
openalex +1 more source
MLDAS: Machine Learning Dynamic Algorithm Selection for Software‐Defined Networking Security
ABSTRACT Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning (ML) algorithms with Software‐Defined Networking (SDN) controllers to enhance network security through adaptive ...
Pablo Benlloch +3 more
wiley +1 more source
Task offloading decision making for IoV based on deep reinforcement learning. [PDF]
Su J, Liu Y.
europepmc +1 more source

