Results 131 to 140 of about 57,166 (309)

Self-Protected Virtual Sensor Network for Microcontroller Fault Detection. [PDF]

Sensors (Basel), 2022
Sternharz G, Skackauskas J, Elhalwagy A, Grichnik AJ, Kalganova T, Huda MN.   +5 more
europepmc   +1 more source

Extending sensor networks into the Cloud using Amazon Web Services

, 2010
Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications ...
Kevin Lee, Lee, Kevin, Danny Hughes, Lee, K, David Murray, Hughes, D., Hughes, Danny, Joosen, W., Murray, D, Joosen, W, Wouter Joosen, Hughes, D, Murray, D., Lee, K., Murray, Dave, Joosen, Wouter   +15 more
core   +1 more source

Measuring human trust in a virtual assistant using physiological sensing in virtual reality

, 2020
With the advancement of Artificial Intelligence technology to make smart devices, understanding how humans develop trust in virtual agents is emerging as a critical research field.
Billinghurst, M., Duenser, A., Pai, Y.S., Lochner, M., Hajika, R., Gupta, K.   +5 more
core   +1 more source

An Imaging‐Guided, Patient‐Specific Guiding Aid (RWNGuide) for Safe and Reproducible Inner Ear Drug Delivery

Advanced Materials Technologies, EarlyView.
A patient‐specific, imaging‐guided aid enables precise and reproducible drug delivery to the inner ear. By guiding therapeutic agents directly to the round window niche, this approach reduces variability in drug localization, improves delivery safety, and addresses a critical bottleneck in inner ear therapy, offering a scalable strategy for precision ...
Yanjing Luo, Shanshan Jiang, Yimian Luo, Adele Moatti, Farnaz Matin‐Mann   +4 more
wiley   +1 more source

A New Method for Spatial Estimation of Water Quality Using an Optimal Virtual Sensor Network and In Situ Observations: A Case Study of Chemical Oxygen Demand. [PDF]

Sensors (Basel), 2023
Zhao N.
europepmc   +1 more source

The Evolution of Aerosol Jet Printing, A Review: Enhancing Material Versatility and Improvements for Next‐Generation Applications

Advanced Materials Technologies, EarlyView.
Aerosol Jet Printing (AJP) has emerged as a versatile additive manufacturing technique for high‐resolution, conformal, and multi‐material printing. This review highlights advances in printable materials, substrate compatibility, post‐processing, characterization, and process innovations, while critically discussing current challenges and future ...
Chandrachur Chatterjee, Rocco Lupoi, Michael J. Gibbons   +2 more
wiley   +1 more source

Machine Learning for Enhanced Operation of Underperforming Sensors in Humid Conditions

Proceedings
Using a single sensor as a virtual electronic nose, we demonstrate the possibility of obtaining good results with underperforming sensors that, at first glance, would be discarded.
Guillem Domènech-Gil, Donatella Puglisi
doaj   +1 more source

Development of a Virtual Sensor for Real-Time Prediction of Granule Flow Properties. [PDF]

ESCAPE, 2022
Lagare RB, da Conceicao MA, Camille Acevedo Rosario A, Leigh Young K, Huang YS, Sheriff MZ, Clementson C, Mort P, Nagy Z, Reklaitis GV.   +9 more
europepmc   +1 more source

Surface‐Plasmon‐Coupled Blue InGaN/GaN Micro‐LEDs with Oxide–Metal–Oxide Capping Layer Compatible to Chip Fabrication Process

Advanced Optical Materials, EarlyView.
A sidewall‐integrated oxide–metal–oxide architecture is demonstrated to overcome efficiency degradation in ultra‐small InGaN/GaN micro‐LEDs. Conformal Al2O3 passivation combined with plasmonic Ag nanoparticles enables localized surface plasmon–exciton coupling, converting surface‐related nonradiative losses into radiative emission.
Pil‐Kyu Jang, Lee‐Woon Jang, Ohbin Kwon, Yeong‐Hoon Cho, Sangbum Kim, Sang‐Ik Lee, Seungjae Baek, Jiwon Park, Myeongjun Choi, Jaeseung Kim, Taehwan Kim, Sung‐Un Kim, Min‐Seok Lee, Yong‐Ho Ra, Ki Hoon Nam, Seung Min Kwak, Alexander Y. Polyakov, In‐Hwan Lee   +17 more
wiley   +1 more source

Virtual Sensor for Estimating the Strain-Hardening Rate of Austenitic Stainless Steels Using a Machine Learning Approach

Applied Sciences
This study introduces a Multiple Linear Regression (MLR) model that functions as a virtual sensor for estimating the strain-hardening rate of austenitic stainless steels, represented by the Hardening Rate of Hot rolled and annealed Stainless steel sheet (
Julia Contreras-Fortes, M. Inmaculada Rodríguez-García, David L. Sales, Rocío Sánchez-Miranda, Juan F. Almagro, Ignacio Turias   +5 more
doaj   +1 more source