Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Aurea Soriano-Vargas"'
Autor:
Manuel Castro, Pedro Ribeiro Mendes Júnior, Aurea Soriano-Vargas, Rafael de Oliveira Werneck, Maiara Moreira Gonçalves, Leopoldo Lusquino Filho, Renato Moura, Marcelo Zampieri, Oscar Linares, Vitor Ferreira, Alexandre Ferreira, Alessandra Davólio, Denis Schiozer, Anderson Rocha
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-18 (2023)
Abstract Inferring causal relationships from observational data is a key challenge in understanding the interpretability of Machine Learning models. Given the ever-increasing amount of observational data available in many areas, Machine Learning algo
Externí odkaz:
https://doaj.org/article/b28347ad19fb496e8d9465157c4e12e8
Autor:
Aurea Soriano-Vargas, Klaus Rollmann, Denis José Schiozer, Alessandra Davolio, Forlan La Rosa Almeida, Anderson Rocha
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 52:3052-3065
We propose a novel approach based on Deep Learning methods using a convolutional neural networks (CNNs) to compare observed four-dimensional (4-D) seismic data with reservoir simulation model results and select the simulation models with the best mat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12e55980fb13ffaaf234d7d3b8338657
https://doi.org/10.1109/tsmc.2021.3051649
https://doi.org/10.1109/tsmc.2021.3051649
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
We present an integrated interactive framework for the visual analysis of time-varying multivariate data sets. As part of our research, we performed in-depth studies concerning the applicability of visualization techniques to obtain valuable insights
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11989ac48b18d0adb9d982b527685ee0
https://doi.org/10.1177/1473871619858937
https://doi.org/10.1177/1473871619858937
Supplementary Material and datasets of the paper Manifold Learning for Real-World Event Understanding. It includes 5 datasets: - Wedding: royal wedding which happened on April 29th, 2011 at the Westminster Abbey; - Fire: Notre Dame cathedral fire whi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a9185429569a84a6bacea6930ff5888
Autor:
Alessandra Davolio, Aurea Soriano-Vargas, Denis José Schiozer, Bernd Hamann, Forlan La Rosa Almeida, Anderson Rocha, Klaus Rollmann
Publikováno v:
Day 5 Fri, July 31, 2020.
Numerical simulations use past reservoir behavior to calibrate models used to predict future performance. Traditionally, this process is carried out deterministically through history matching and most current approaches focus on developing probabilis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5541e72058dab0d8e6553f1a962f62a6
https://doi.org/10.2118/199099-ms
https://doi.org/10.2118/199099-ms
Autor:
Anderson Rocha, Marcos Vinicius Mussel Cirne, Allan Pinto, Bahram Lavi, Aurea Soriano-Vargas, Luis A. M. Pereira, Alexandre Ferreira, Fernanda A. Andaló
Publikováno v:
Deep Biometrics ISBN: 9783030325824
Biometric systems are prevalent in access control but are vulnerable to frauds. A typical attempt of violating them is through presentation attacks, in which synthetic data is directly presented to an acquisition sensor to deceive these systems. A we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0399e11dd78fad72a23208f65ea72621
https://doi.org/10.1007/978-3-030-32583-1_13
https://doi.org/10.1007/978-3-030-32583-1_13
Autor:
Rafael de Oliveira Werneck, Raphael Prates, Renato Moura, Maiara Moreira Gonçalves, Manuel Castro, Aurea Soriano-Vargas, Pedro Ribeiro Mendes Júnior, M. Manzur Hossain, Marcelo Ferreira Zampieri, Alexandre Ferreira, Alessandra Davólio, Denis Schiozer, Anderson Rocha
Publikováno v:
Journal of Petroleum Science and Engineering. 210:109937
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::681717e0fb4a68eff7ef3b4fb90adc57
https://doi.org/10.1016/j.petrol.2021.109937
https://doi.org/10.1016/j.petrol.2021.109937
Autor:
Aurea Soriano-Vargas, Denis José Schiozer, Alessandra Davolio, Marcos Vinicius Mussel Cirne, Klaus Rollmann, Anderson Rocha
Publikováno v:
Journal of Petroleum Science and Engineering. 208:109260
Four-dimensional seismic (4DS) contains spatial information that provides insights into the location, shape, and movement of fluids (oil, gas, water). It helps engineers to adjust reservoir simulation models and increase their capability of providing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2fb270d1c0339b3ddcc7741818c1460
https://doi.org/10.1016/j.petrol.2021.109260
https://doi.org/10.1016/j.petrol.2021.109260
Autor:
Alexandre Ferreira, Maiara Moreira Gonçalves, Aurea Soriano-Vargas, Manuel Castro, Denis José Schiozer, M. F. Zampieri, Raphael Prates, Bernd Hamann, Anderson Rocha, Pedro Ribeiro Mendes Júnior, Manzur Hossain, Rafael de Oliveira Werneck, Renato Lopes Moura, Alessandra Davolio
Publikováno v:
Journal of Petroleum Science and Engineering. 206:108988
Detecting anomalies in time series data of hydrocarbon reservoir production is crucially important. Anomalies can result for different reasons: gross errors, system availability, human intervention, or abrupt changes in the series. They must be ident
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63592fae274a878f12af419b1aba8792
https://doi.org/10.1016/j.petrol.2021.108988
https://doi.org/10.1016/j.petrol.2021.108988
Autor:
Bruno César Vani, Bernd Hamann, Milton Hirokazu Shimabukuro, João Francisco Galera Monico, Aurea Soriano-Vargas, Maria Cristina Ferreira de Oliveira
Publikováno v:
Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Made available in DSpace on 2018-12-11T17:14:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-11-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56c27290e403ebb756014debb8fd2047
https://doi.org/10.1016/j.cag.2017.08.013
https://doi.org/10.1016/j.cag.2017.08.013