Zobrazeno 1 - 10
of 4 798
pro vyhledávání: '"Stefanou A"'
Publikováno v:
Clinical Ophthalmology, Vol Volume 18, Pp 1841-1849 (2024)
Kinga Dabrowska-Kloda,1 Eydis Olafsdottir,1 Anastasia Stefanou,1 Sven Crafoord1,2 1Department of Ophthalmology, Örebro University Hospital, Örebro, Sweden; 2Department of Ophthalmology, Faculty of Medicine and Health, Örebro University, Örebro, S
Externí odkaz:
https://doaj.org/article/1b128e16265547dab77bbec752759401
This paper introduces a novel approach that combines Proper Orthogonal Decomposition (POD) with Thermodynamics-based Artificial Neural Networks (TANN) to capture the macroscopic behavior of complex inelastic systems and derive macroelements in geomec
Externí odkaz:
http://arxiv.org/abs/2408.07165
Deep Geothermal Energy, Carbon Capture and Storage, and Hydrogen Storage hold considerable promise for meeting the energy sector's large-scale requirements and reducing CO$_2$ emissions. However, the injection of fluids into the Earth's crust, essent
Externí odkaz:
http://arxiv.org/abs/2408.03664
Autor:
Morsel, Ahmad, Masi, Filippo, Marché, Emmanuel, Racineux, Guillaume, Kotronis, Panagiotis, Stefanou, Ioannis
We present a novel experimental setup called miniBLAST, which enables systematic and repeatable laboratory tests of structures subjected to blast loads. The explosive source is based on the discharge of high electrical loads on a thin conductor, prod
Externí odkaz:
http://arxiv.org/abs/2408.01586
This study investigates the potential accuracy boundaries of physics-informed neural networks, contrasting their approach with previous similar works and traditional numerical methods. We find that selecting improved optimization algorithms significa
Externí odkaz:
http://arxiv.org/abs/2405.04230
Autor:
Grimpen, Fritz, Stefanou, Anastasios
Given a multiparameter filtration of simplicial complexes, we consider the problem of explicitly constructing generators for the multipersistent homology groups with arbitrary PID coefficients. We propose the use of spanning trees as a tool to identi
Externí odkaz:
http://arxiv.org/abs/2312.00235
Autor:
Garyfallou, Dimitrios, Stefanou, Athanasios, Giamouzis, Christos, Antoniadis, Moschos, Chararas, Georgios, Chatzis, Konstantinos, Samaras, Dimitris, Themeli, Rafaela, Michailidis, Anastasios, Gogolou, Vasiliki, Zachos, Nikos, Evmorfopoulos, Nestor, Noulis, Thomas, Pavlidis, Vasilis F., Hatzopoulos, Alkiviadis, Chatzineofytou, Elpida, Moisiadis, Yiannis
Model order reduction (MOR) is crucial for the design process of integrated circuits. Specifically, the vast amount of passive RLCk elements in electromagnetic models extracted from physical layouts exacerbates the extraction time, the storage requir
Externí odkaz:
http://arxiv.org/abs/2401.10236
In this paper, we introduce the persistence transformation, a novel methodology in Topological Data Analysis (TDA) for applications in time series data which can be obtained in various areas such as science, politics, economy, healthcare, engineering
Externí odkaz:
http://arxiv.org/abs/2310.05559
Deep Geothermal Energy, Carbon Capture, and Storage and Hydrogen Storage have significant potential to meet the large-scale needs of the energy sector and reduce the CO$_2$ emissions. However, the injection of fluids into the earth's crust, upon whic
Externí odkaz:
http://arxiv.org/abs/2310.02700
Publikováno v:
Monthly Notices of the Royal Astronomical Society, Volume 526, Issue 1, November 2023, Pages 1504-1511
In this study, Physics-Informed Neural Networks (PINNs) are skilfully applied to explore a diverse range of pulsar magneto-spheric models, specifically focusing on axisymmetric cases. The study successfully reproduced various axisymmetric models foun
Externí odkaz:
http://arxiv.org/abs/2309.06410