[HTML][HTML] Condition monitoring using machine learning: A review of theory, applications, and recent advances
In modern industry, the quality of maintenance directly influences equipment's operational
uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive …
uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive …
Latest research trends in gait analysis using wearable sensors and machine learning: A systematic review
Gait is the locomotion attained through the movement of limbs and gait analysis examines
the patterns (normal/abnormal) depending on the gait cycle. It contributes to the …
the patterns (normal/abnormal) depending on the gait cycle. It contributes to the …
Artificial neural networks-based intrusion detection system for internet of things fog nodes
The Internet of Things (IoT) represents a mean to share resources (memory, storage
computational power, data, etc.) between computers and mobile devices, as well as …
computational power, data, etc.) between computers and mobile devices, as well as …
A comparison of various supervised machine learning techniques for prostate cancer prediction
Prostate cancer is a kind of cancer that is seen worldwide and causes death of many people.
Early diagnosis of cancer helps patients during the treatment phase. For this reason, cancer …
Early diagnosis of cancer helps patients during the treatment phase. For this reason, cancer …
Application of graph learning with multivariate relational representation matrix in vehicular social networks
The essence of connection in vehicle network is the social relationship between people, and
thus Vehicular Social Networks (VSNs), characterized by social aspects and features, can …
thus Vehicular Social Networks (VSNs), characterized by social aspects and features, can …
High-Speed Nonlinear Circuit Macromodeling Using Hybrid-Module Clockwork Recurrent Neural Network
F Charoosaei, A Faraji, SA Sadrossadat… - … on Circuits and …, 2023 - ieeexplore.ieee.org
In the computer-aided design (CAD) area, the recurrent neural network (RNN) has shown
notable functionality in generating fast and high-performance models rather than the models …
notable functionality in generating fast and high-performance models rather than the models …
Artificial intelligence and machine learning algorithms in the detection of heavy metals in water and wastewater: Methodological and ethical challenges
BM Maurya, N Yadav, T Amudha, J Satheeshkumar… - Chemosphere, 2024 - Elsevier
Heavy metals (HMs) enter waterbodies through various means, which, when exceeding a
threshold limit, cause toxic effects both on the environment and in humans upon entering …
threshold limit, cause toxic effects both on the environment and in humans upon entering …
Anomaly behavior analysis for IoT network nodes
The Internet of Things (IoT) will connect not only computers and mobile devices, but it will
also interconnect smart buildings, homes, and cities. The integration of IoT with Fog and …
also interconnect smart buildings, homes, and cities. The integration of IoT with Fog and …
Visual interpretation of CNN decision-making process using Simulated Brain MRI
Convolutional neural networks (CNNs) are being extensively used to analyze medical
images given the remarkable performances achieved so far. Due to the non-transparent …
images given the remarkable performances achieved so far. Due to the non-transparent …
A Spiking Neuromorphic Architecture Using Gated-RRAM for Associative Memory
A Jones, A Ruen, R Jha - ACM Journal on Emerging Technologies in …, 2021 - dl.acm.org
This work reports a spiking neuromorphic architecture for associative memory simulated in a
SPICE environment using recently reported gated-RRAM (resistive random-access memory) …
SPICE environment using recently reported gated-RRAM (resistive random-access memory) …