Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …
interconnected devices, allowing the use of various smart applications. The enormous …
Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
Logistic regression for machine learning in process tomography
The main goal of the research presented in this paper was to develop a refined machine
learning algorithm for industrial tomography applications. The article presents algorithms …
learning algorithm for industrial tomography applications. The article presents algorithms …
A review on applications of time-lapse electrical resistivity tomography over the last 30 years: Perspectives for mining waste monitoring
Mining operations generate large amounts of wastes which are usually stored into large-
scale storage facilities which pose major environmental concerns and must be properly …
scale storage facilities which pose major environmental concerns and must be properly …
Real-time prediction of nuclear power plant parameter trends following operator actions
J Bae, G Kim, SJ Lee - Expert Systems with Applications, 2021 - Elsevier
Operators in the main control room of a nuclear power plant (NPP) oversee all plant
operations, and thus any human error committed by the operators can be critical. If the …
operations, and thus any human error committed by the operators can be critical. If the …
[PDF][PDF] Assessment model of cutting tool condition for real-time supervision system
E KozłowsKi, D MAzurKiEwicz… - Eksploatacja i …, 2019 - bibliotekanauki.pl
Further development of manufacturing technology, in particular machining requires the
search for new innovative technological solutions. This applies in particular to the advanced …
search for new innovative technological solutions. This applies in particular to the advanced …
Numerical solution of inverse problems by weak adversarial networks
In this paper, a weak adversarial network approach is developed to numerically solve a
class of inverse problems, including electrical impedance tomography and dynamic …
class of inverse problems, including electrical impedance tomography and dynamic …
[HTML][HTML] AI energized hydrogel design, optimization and application in biomedicine
Z Li, P Song, G Li, Y Han, X Ren, L Bai, J Su - Materials Today Bio, 2024 - Elsevier
Traditional hydrogel design and optimization methods usually rely on repeated experiments,
which is time-consuming and expensive, resulting in a slow-moving of advanced hydrogel …
which is time-consuming and expensive, resulting in a slow-moving of advanced hydrogel …
Comparison of machine learning methods for image reconstruction using the LSTM classifier in industrial electrical tomography
Electrical tomography is a non-invasive method of monitoring the interior of objects, which is
used in various industries. In particular, it is possible to monitor industrial processes inside …
used in various industries. In particular, it is possible to monitor industrial processes inside …
Quality assessment of the neural algorithms on the example of EIT-UST hybrid tomography
The paper presents the results of research on the hybrid industrial tomograph electrical
impedance tomography (EIT) and ultrasonic tomography (UST)(EIT-UST), operating on the …
impedance tomography (EIT) and ultrasonic tomography (UST)(EIT-UST), operating on the …