Zobrazeno 1 - 10
of 81 431
pro vyhledávání: '"Carmo AS"'
Autor:
Lopes, Rovan F., Tumelero, Milton A., de Araujo, Clodoaldo I. L., de Andrade, Antonio M. H., Mesquita, Fabiano, Carmo, Danusa, Colauto, F., Ortiz, W. A., Pureur, P.
The magnetic textures generated by a perpendicularly applied magnetic field at the ferromagnetic layer of $Co/Al_{2}O_{3}/Nb$ thin film heterostructures are investigated using magneto-optical imaging and micromagnetic simulations. It is observed that
Externí odkaz:
http://arxiv.org/abs/2410.18028
In this article, we present the mathematical analysis of the convergence of the linearized Crank-Nicolson Galerkin method for a nonlinear Schrodinger problem related to a domain with a moving boundary. The convergence analysis of the numerical method
Externí odkaz:
http://arxiv.org/abs/2410.08910
This paper investigates whether large language models (LLMs) are state-of-the-art quality estimators for machine translation of user-generated content (UGC) that contains emotional expressions, without the use of reference translations. To achieve th
Externí odkaz:
http://arxiv.org/abs/2410.06338
Autor:
Carmo, Félix do, Kanojia, Diptesh
The tutorial describes the concept of edit distances applied to research and commercial contexts. We use Translation Edit Rate (TER), Levenshtein, Damerau-Levenshtein, Longest Common Subsequence and $n$-gram distances to demonstrate the frailty of st
Externí odkaz:
http://arxiv.org/abs/2410.05881
Machine translation (MT) of user-generated content (UGC) poses unique challenges, including handling slang, emotion, and literary devices like irony and sarcasm. Evaluating the quality of these translations is challenging as current metrics do not fo
Externí odkaz:
http://arxiv.org/abs/2410.03277
Autor:
Carmo, Marciano Palma do, Mack, David, Roth, Diane J., Zhao, Miao, Devis, Ancin M., Rodríguez-Fortuño, Francisco J., Maier, Stefan A., Huidobro, Paloma A., Rakovich, Aliaksandra
Controlled long-range transport of micro- and nano-scale objects is a key requirement in lab-on-a-chip and microfluidic applications, enabling the efficient capture, concentration, manipulation, and detection of analytes. Traditional methods such as
Externí odkaz:
http://arxiv.org/abs/2408.00515
The use of machine learning algorithms to investigate phase transitions in physical systems is a valuable way to better understand the characteristics of these systems. Neural networks have been used to extract information of phases and phase transit
Externí odkaz:
http://arxiv.org/abs/2404.15118
Identifying and characterizing brain fiber bundles can help to understand many diseases and conditions. An important step in this process is the estimation of fiber orientations using Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI). However, o
Externí odkaz:
http://arxiv.org/abs/2402.11775
Autor:
Carmo, Diedre S., Ribeiro, Jean A., Comellas, Alejandro P., Reinhardt, Joseph M., Gerard, Sarah E., Rittner, Letícia, Lotufo, Roberto A.
The COVID-19 pandemic response highlighted the potential of deep learning methods in facilitating the diagnosis, prognosis and understanding of lung diseases through automated segmentation of pulmonary structures and lesions in chest computed tomogra
Externí odkaz:
http://arxiv.org/abs/2312.02365
Autor:
Carmo, Diedre S., Tudas, Rosarie A., Comellas, Alejandro P., Rittner, Leticia, Lotufo, Roberto A., Reinhardt, Joseph M., Gerard, Sarah E.
Automated segmentation of lung abnormalities in computed tomography is an important step for diagnosing and characterizing lung disease. In this work, we improve upon a previous method and propose S-MEDSeg, a deep learning based approach for accurate
Externí odkaz:
http://arxiv.org/abs/2310.09446