Zobrazeno 1 - 10
of 22 414
pro vyhledávání: '"Bessa SO"'
Autor:
Onório, Duanny Silva, Marques, Flavio A. M., Cotta, Alexandre A. C., Tsuchida, Jefferson E., Santos, Alexandre Bessa dos, Osório, Jonas H.
Hollow-core photonic crystal fibers (HCPCFs) have become a key enabling technology for addressing a broad spectrum of fundamental and applied needs. Indeed, recent advancements achieved by the HCPCF research community have led to significant progress
Externí odkaz:
http://arxiv.org/abs/2412.05089
In the pursuit of designing safer and more efficient energy-absorbing structures, engineers must tackle the challenge of improving crush performance while balancing multiple conflicting objectives, such as maximising energy absorption and minimising
Externí odkaz:
http://arxiv.org/abs/2411.14508
Autor:
Coutinho, Pedro Henrique Silva, Bessa, Iury, Rodrigues, Victor Hugo Pereira, Oliveira, Tiago Roux
This paper deals with sliding mode control for multivariable polytopic uncertain systems. We provide systematic procedures to design variable structure controllers (VSCs) and unit-vector controllers (UVCs). Based on suitable representations for the c
Externí odkaz:
http://arxiv.org/abs/2411.10592
Measurements of the redshift drift -- the real time variation of the redshift of distance sources -- are expected in the next couple of decades using next generation facilities such as the ANDES spectrograph at the ELT and the SKAO survey. The unprec
Externí odkaz:
http://arxiv.org/abs/2409.09977
Autor:
Salimi, Salma, Salimpour, Sahar, Queralta, Jorge Peña, Bessa, Wallace Moreira, Westerlund, Tomi
Human pose estimation involves detecting and tracking the positions of various body parts using input data from sources such as images, videos, or motion and inertial sensors. This paper presents a novel approach to human pose estimation using machin
Externí odkaz:
http://arxiv.org/abs/2408.15717
Additive manufacturing methods together with topology optimization have enabled the creation of multiscale structures with controlled spatially-varying material microstructure. However, topology optimization or inverse design of such structures in th
Externí odkaz:
http://arxiv.org/abs/2408.13843
Lagrangian decomposition (LD) is a relaxation method that provides a dual bound for constrained optimization problems by decomposing them into more manageable sub-problems. This bound can be used in branch-and-bound algorithms to prune the search spa
Externí odkaz:
http://arxiv.org/abs/2408.12695
Multi-fidelity machine learning methods address the accuracy-efficiency trade-off by integrating scarce, resource-intensive high-fidelity data with abundant but less accurate low-fidelity data. We propose a practical multi-fidelity strategy for probl
Externí odkaz:
http://arxiv.org/abs/2407.15110
Neural networks (NNs) hold great promise for advancing inverse design via topology optimization (TO), yet misconceptions about their application persist. This article focuses on neural topology optimization (neural TO), which leverages NNs to reparam
Externí odkaz:
http://arxiv.org/abs/2407.13954
Autor:
Hamann, Hendrik F., Brunschwiler, Thomas, Gjorgiev, Blazhe, Martins, Leonardo S. A., Puech, Alban, Varbella, Anna, Weiss, Jonas, Bernabe-Moreno, Juan, Massé, Alexandre Blondin, Choi, Seong, Foster, Ian, Hodge, Bri-Mathias, Jain, Rishabh, Kim, Kibaek, Mai, Vincent, Mirallès, François, De Montigny, Martin, Ramos-Leaños, Octavio, Suprême, Hussein, Xie, Le, Youssef, El-Nasser S., Zinflou, Arnaud, Belyi, Alexander J., Bessa, Ricardo J., Bhattarai, Bishnu Prasad, Schmude, Johannes, Sobolevsky, Stanislav
Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets through self-supervision. The resulting rich representations of complex syst
Externí odkaz:
http://arxiv.org/abs/2407.09434