Zobrazeno 1 - 10
of 8 894
pro vyhledávání: '"Sotiropoulos, A"'
The paper presents a cradle-to-gate sustainability assessment methodology specifically designed to evaluate aircraft components in a robust and systematic manner. This methodology integrates multi-criteria decision-making (MCDM) analysis across ten c
Externí odkaz:
http://arxiv.org/abs/2412.07421
Rolling element bearings are critical components of rotating machinery, with their performance directly influencing the efficiency and reliability of industrial systems. At the same time, bearing faults are a leading cause of machinery failures, ofte
Externí odkaz:
http://arxiv.org/abs/2412.01322
Publikováno v:
2024 Sixth International Conference on Intelligent Computing in Data Sciences (ICDS), Marrakech, Morocco, 2024, pp. 1-8
Metaheuristic algorithms are essential for solving complex optimization problems in different fields. However, the difficulty in comparing and rating these algorithms remains due to the wide range of performance metrics and problem dimensions usually
Externí odkaz:
http://arxiv.org/abs/2409.11617
Autor:
Aretos, E. V., Sotiropoulos, D. G.
In today's era, Neural Networks (NN) are applied in various scientific fields such as robotics, medicine, engineering, etc. However, the predictions of neural networks themselves contain a degree of uncertainty that must always be taken into account
Externí odkaz:
http://arxiv.org/abs/2409.05206
In this work, we continue the investigation of certain enrichments of dual algebraic structures in monoidal double categories, that was initiated in [Vas19]. First, we re-visit monads and comonads in double categories and establish a tensored and cot
Externí odkaz:
http://arxiv.org/abs/2408.03180
Autor:
Zhang, Zexia, Anjiraki, Mehrshad Gholami, Seyedzadeh, Hossein, Sotiropoulos, Fotis, Khosronejad, Ali
Flood-induced deformation of the bed topography of fluvial meandering rivers could lead to river bank displacement, structural failure of the infrastructures, and the propagation of scour or deposition features. The assessment of sediment transport i
Externí odkaz:
http://arxiv.org/abs/2407.18359
This study introduces a novel approach for learning mixtures of Markov chains, a critical process applicable to various fields, including healthcare and the analysis of web users. Existing research has identified a clear divide in methodologies for l
Externí odkaz:
http://arxiv.org/abs/2405.15094
Autor:
Santoni, Christian, Zhang, Dichang, Zhang, Zexia, Samaras, Dimitris, Sotiropoulos, Fotis, Khosronejad, Ali
This study proposes a novel machine learning (ML) methodology for the efficient and cost-effective prediction of high-fidelity three-dimensional velocity fields in the wake of utility-scale turbines. The model consists of an auto-encoder convolutiona
Externí odkaz:
http://arxiv.org/abs/2404.07938
In this work, we introduce a novel evaluation framework for generative models of graphs, emphasizing the importance of model-generated graph overlap (Chanpuriya et al., 2021) to ensure both accuracy and edge-diversity. We delineate a hierarchy of gra
Externí odkaz:
http://arxiv.org/abs/2312.03691
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach
Given a complex graph database of node- and edge-attributed multi-graphs as well as associated metadata for each graph, how can we spot the anomalous instances? Many real-world problems can be cast as graph inference tasks where the graph representat
Externí odkaz:
http://arxiv.org/abs/2311.07355