Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications

RA Khalil, N Saeed, M Masood, YM Fard… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
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 …

Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions

S Latif, M Driss, W Boulila, ZE Huma, SS Jamal… - Sensors, 2021 - mdpi.com
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …

Logistic regression for machine learning in process tomography

T Rymarczyk, E Kozłowski, G Kłosowski, K Niderla - Sensors, 2019 - mdpi.com
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 …

A review on applications of time-lapse electrical resistivity tomography over the last 30 years: Perspectives for mining waste monitoring

A Dimech, LZ Cheng, M Chouteau, J Chambers… - Surveys in …, 2022 - Springer
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 …

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 …

[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 …

Numerical solution of inverse problems by weak adversarial networks

G Bao, X Ye, Y Zang, H Zhou - Inverse Problems, 2020 - iopscience.iop.org
In this paper, a weak adversarial network approach is developed to numerically solve a
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 …

Comparison of machine learning methods for image reconstruction using the LSTM classifier in industrial electrical tomography

G Kłosowski, T Rymarczyk, K Niderla, M Rzemieniak… - Energies, 2021 - mdpi.com
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 …

Quality assessment of the neural algorithms on the example of EIT-UST hybrid tomography

G Kłosowski, T Rymarczyk, T Cieplak, K Niderla… - Sensors, 2020 - mdpi.com
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 …