Results 131 to 140 of about 33,353 (245)

Advancing Flexible Pressure Sensors for Next‐Generation Medical Monitoring

open access: yesAdvanced Sensor Research, Volume 5, Issue 6, June 2026.
This review highlights recent advances in flexible pressure sensors for next‐generation medical monitoring. The sensing mechanisms, material and structural optimization strategies, and intelligent algorithms are systematically summarized. Emerging applications in cardiovascular, respiratory, neurological, laryngeal, and ocular disease monitoring are ...
Chunjun Su   +4 more
wiley   +1 more source

An In‐Line Machine Vision–Based Profilometry Tool for Non‐Destructive Thickness Assessment of Perovskite Films

open access: yesAdvanced Electronic Materials, Volume 12, Issue 11, 8 June 2026.
This work proposes a machine‐vision‐based tool for predicting the thickness of in‐line deposited perovskite films, enabling real‐time decision making to control deposition parameters. The workflow integrates perovskite deposition and annealing with uniformity analysis and minimodule fabrication.
Juan Pablo Velásquez   +9 more
wiley   +1 more source

Assessing the Diagnostic Performance of a Smart Bra Using Temperature and Bioimpedance for Breast Cancer Detection: A First-in-Human Study. [PDF]

open access: yesSensors (Basel)
Belmont AS   +9 more
europepmc   +1 more source

The Path to Future‐Proof Photovoltaics in Europe: Current Status and Impact of Technological Innovation on Reliable and Bankable Photovoltaics

open access: yesAdvanced Energy and Sustainability Research, Volume 7, Issue 6, June 2026.
This article provides an overview of the current state of the art and future improvements in PV technology and explains how changes in the technology and design of individual PV components—at the module level, the balance‐of‐system (BOS) level, or the PV plant level—can affect the reliability, durability, and energy output of a PV system.
Ulrike Jahn   +10 more
wiley   +1 more source

Real‐Time Data‐Driven Fault Diagnosis of Photovoltaic Arrays Using an Edge‐Server Machine‐Learning Framework

open access: yesEnergy Science &Engineering, Volume 14, Issue 6, Page 2961-2982, June 2026.
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan   +4 more
wiley   +1 more source

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