Zobrazeno 1 - 10
of 4 560
pro vyhledávání: '"A. Fister"'
Digital twins belong to ten of the strategic technology trends according to the Gartner list from 2019, and have encountered a big expansion, especially with the introduction of Industry 4.0. Sport, on the other hand, has become a constant companion
Externí odkaz:
http://arxiv.org/abs/2407.11990
Autor:
Lippertz, Gertjan, Breunig, Oliver, Fister, Rafael, Uday, Anjana, Bliesener, Andrea, Brede, Jens, Taskin, Alexey, Ando, Yoichi
The selective-area epitaxy (SAE) is a useful technique to grow epitaxial films with a desired shape on a pre-patterned substrate. Although SAE of patterned topological-insulator (TI) thin films has been performed in the past, there has been no report
Externí odkaz:
http://arxiv.org/abs/2404.08427
Much debate nowadays is devoted to the impacts of modern information and communication technology on global carbon emissions. Green information and communication technology is a paradigm creating a sustainable and environmentally friendly computing f
Externí odkaz:
http://arxiv.org/abs/2401.01782
Numerical association rule mining is a widely used variant of the association rule mining technique, and it has been extensively used in discovering patterns and relationships in numerical data. Initially, researchers and scientists integrated numeri
Externí odkaz:
http://arxiv.org/abs/2307.00662
Autor:
Fister Jr., Iztok, Fister, Iztok
The main deficiency of the algorithms running on digital computers nowadays is their inability to change themselves during the execution. In line with this, the paper introduces the so-called replicated algorithms, inspired by the concept of developi
Externí odkaz:
http://arxiv.org/abs/2304.13524
Association rule mining is intended for searching for the relationships between attributes in transaction databases. The whole process of rule discovery is very complex, and involves pre-processing techniques, a rule mining step, and post-processing,
Externí odkaz:
http://arxiv.org/abs/2302.12594
Numerical association rule mining offers a very efficient way of mining association rules, where algorithms can operate directly with categorical and numerical attributes. These methods are suitable for mining different transaction databases, where d
Externí odkaz:
http://arxiv.org/abs/2212.03669
Autor:
J. Pérez-Aracil, D. Fister, C.M. Marina, C. Peláez-Rodríguez, L. Cornejo-Bueno, P.A. Gutiérrez, M. Giuliani, A. Castelleti, S. Salcedo-Sanz
Publikováno v:
Applied Computing and Geosciences, Vol 23, Iss , Pp 100185- (2024)
This paper proposes two hybrid approaches based on Autoencoders (AEs) for long-term temperature prediction. The first algorithm comprises an AE trained to learn temperature patterns, which is then linked to a second AE, used to detect possible anomal
Externí odkaz:
https://doaj.org/article/e45536aa007d458391e2e43ee37b08a9
Publikováno v:
eLife, Vol 13 (2024)
Epithelial damage leads to early reactive oxygen species (ROS) signaling, which regulates sensory neuron regeneration and tissue repair. How the initial type of tissue injury influences early damage signaling and regenerative growth of sensory axons
Externí odkaz:
https://doaj.org/article/70015889c95a4e84bfc6ec955eb3bb3a
Autor:
Fister, Dušan, Pérez-Aracil, Jorge, Peláez-Rodríguez, César, Del Ser, Javier, Salcedo-Sanz, Sancho
In this paper three customised Artificial Intelligence (AI) frameworks, considering Deep Learning (convolutional neural networks), Machine Learning algorithms and data reduction techniques are proposed, for a problem of long-term summer air temperatu
Externí odkaz:
http://arxiv.org/abs/2209.15424