Aurea Rossy Soriano Vargas

Pós-doutorado

Formação complementar

Idiomas

Áreas de atuação

Participação em eventos

Participação em bancas

Produções bibliográficas

• SORIANO-VARGAS, Aurea ; ROLLMANN, KLAUS ; ALMEIDA, FORLAN ; DAVOLIO, ALESSANDRA ; HAMANN, BERND ; SCHIOZER, DENIS J. ; ROCHA, ANDERSON . A synthetic case study of measuring the misfit between 4D seismic data and numerical reservoir simulation models through the Momenta Tree. COMPUTERS & GEOSCIENCES , v. 145, p. 104617, 2020.

• SORIANO-VARGAS, Aurea ; HAMANN, BERND ; F DE OLIVEIRA, MARIA CRISTINA . TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data. Information Visualization , v. 18, p. 147387161985893, 2019.

• SORIANO-VARGAS, Aurea ; VANI, BRUNO C. ; SHIMABUKURO, MILTON H. ; G. MONICO, JOÃO F. ; F. OLIVEIRA, MARIA CRISTINA ; HAMANN, BERND . Visual analytics of time-varying multivariate ionospheric scintillation data. COMPUTERS & GRAPHICS-UK , v. 68, p. 96-107, 2017.

• ROCHA, A. ; Soriano-Vargas, A. . Deep Biometrics. 1. ed. , 2020.

• SORIANO, AUREA . Visualización Computacional como apoyo en tareas de Mineración de Datos. Revista de Ingeniería de Software, Arequipa, Perú, p. 7 - 8, 01 nov. 2014.

• SORIANO-VARGAS, Aurea ; ROLLMANN, KLAUS ; LA ROSA ALMEIDA, FORLAN ; DAVOLIO, ALESSANDRA ; HAMANN, BERND ; JOSÉ SCHIOZER, DENIS ; ROCHA, ANDERSON . Leveraging Phylogenetic Trees to Assess Variability of Reservoir Models. In: SPE Latin American and Caribbean Petroleum Engineering Conference, 2020, Virtual. SPE Latin American and Caribbean Petroleum Engineering Conference, 2020.

• CUADROS LINARES, OSCAR ; AUREA SORIANO-VARGAS, AUREA ; FAICAL, BRUNO S. ; HAMANN, BERND ; FABRO, ALEXANDRE T. ; J. M. TRAINA, AGMA . Efficient Segmentation of Cell Nuclei in Histopathological Images. In: 2020 IEEE 33rd International Symposium on ComputerBased Medical Systems (CBMS), 2020, Rochester. 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), 2020. p. 47.

• SORIANO, AUREA ; PAULOVICH, FERNANDO ; NONATO, LUIS GUSTAVO ; OLIVEIRA, MARIA CRISTINA F. . Visualization of Music Collections Based on Structural Content Similarity. In: 2014 27th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 2014, Brazil. 2014 27th SIBGRAPI Conference on Graphics, Patterns and Images, 2014. p. 25-32.

• VALVERDE-REBAZA, JORGE ; SORIANO, AUREA ; BERTON, LILIAN ; OLIVEIRA, MARIA CRISTINA FERREIRA DE ; LOPES, ALNEU DE ANDRADE . Music Genre Classification Using Traditional and Relational Approaches. In: 2014 Brazilian Conference on Intelligent Systems (BRACIS), 2014, Sao Paulo. 2014 Brazilian Conference on Intelligent Systems, 2014. p. 259-259-264.

• SORIANO-VARGAS, Aurea . Visualization for Machine Learning. 2020. (Apresentação de Trabalho/Congresso).

• SORIANO-VARGAS, Aurea . Visualization for Machine Learning(III). 2020. (Apresentação de Trabalho/Congresso).

• SORIANO-VARGAS, Aurea . Visualization for Machine Learning (IV). 2020. (Apresentação de Trabalho/Congresso).

• SORIANO-VARGAS, Aurea . Anomaly Detection in Time Series Data.. 2020. (Apresentação de Trabalho/Congresso).

• SORIANO-VARGAS, Aurea . Anomaly Detection in Time Series Data.. 2020. (Apresentação de Trabalho/Congresso).

• SORIANO-VARGAS, Aurea . Visualization for Machine Learning II. 2020. (Apresentação de Trabalho/Congresso).

• SORIANO-VARGAS, Aurea . Presentation attack detection - poster.. 2019. (Apresentação de Trabalho/Conferência ou palestra).

• SORIANO-VARGAS, Aurea . Exploring time-varying multivariate data through a visual analytics framework - poster.. 2019. (Apresentação de Trabalho/Conferência ou palestra).

• SORIANO-VARGAS, Aurea ; MALEKI, M. ; DANAEI, S. ; DAVOLIO, ALESSANDRA ; JOSÉ SCHIOZER, DENIS ; ROCHA, ANDERSON . Machine learning techniques to estimate reservoir property changes directly from 4d seismic attributes and rock property maps.. 2019. (Apresentação de Trabalho/Conferência ou palestra).

• SORIANO-VARGAS, Aurea ; VANI, BRUNO C. ; SHIMABUKURO, MILTON H. ; OLIVEIRA, MARIA CRISTINA F. . Visual analytics of time-varying multivariate ionospheric scintillation data.. 2017. (Apresentação de Trabalho/Conferência ou palestra).

• Soriano, A. . Visualization of music collections based on structural similarity. 2014. (Apresentação de Trabalho/Conferência ou palestra).

• Soriano, A. . Visual Classification of Ionospheric Scintillation Data. 2014. (Apresentação de Trabalho/Seminário).

• Soriano, A. . Music Visualization and Impact of Characteristics Structure of the Traditional and Relational Classification of Music Genres. 2013. (Apresentação de Trabalho/Simpósio).

Projetos de pesquisa

• 2019 - Atual

  Machine-Learning for Analysis of Complex Production Data in a Pre-Salt CarbonateField Project., Situação: Em andamento; Natureza: Pesquisa. , Integrantes: Aurea Rossy Soriano Vargas - Integrante / Anderson Rocha - Coordenador.

• 2018 - Atual

  Similarity Exploration to Measure the Misfit between 4D Seismic Data and Numerical Reservoir Simulation Models, Descrição: Data assimilation is a time-consuming process in reservoir simulation. The outcome of this process is a database employed to estimate and optimize an oil or gas field's production. The process focuses on reducing uncertainty, obtaining numerical reservoir models that plausibly capture the historical dynamic reservoir behavior. Besides the traditional well production data, 4D seismic data are increasingly being used to constrain the uncertainty of numerical reservoir models providing spatial dynamic data. Traditionally, assimilation was qualitative. This approach presented numerous drawbacks, as this process cannot be automated. A current 4DS assimilation focus is the development of practical metrics able to estimate numerically the discrepancies between simulated numerical reservoir models and time-lapse data. We introduce a metric, called Momenta Tree, that uses a set of orthogonal moments in a multi-level data representation, allowing one to compare simulation models with 4D seismic data as images, at different scales and in different domains. The similarity between data is calculated with the Jaccard distance, and it is represented by a phylogenetic tree, where simulated models are represented as circles in branches and their similarity is captured by connections. We validate and compare the new metric with traditional metrics by applying it to a new benchmark introduced in this paper. Additionally, a local application on a more complex case (benchmark built based on real data) is presented. Our results show that best-ranked models using the Momenta Tree presented forecast behavior that encloses the reference data better than the best-ranked models defined using traditional methods.. , Situação: Em andamento; Natureza: Pesquisa. , Alunos envolvidos: Mestrado acadêmico: (1) . , Integrantes: Aurea Rossy Soriano Vargas - Integrante / Anderson Rocha - Coordenador / Klaus Rollmann - Integrante.

• 2013 - 2018

  Visual exploration to support the identification of relevant attributes in time-varying multivariate data, Descrição: Ionospheric scintillation is a rapid variation in the amplitude and/or phase of radio signals traveling through the ionosphere. This spatial and time-varying phenomenon is of interest because its occurrence may affect the reception quality of satellite signals. Specialized receivers at strategic regions can track multiple variables related to the phenomenon, generating a database of historical observations on the regional behavior of ionospheric scintillation. The analysis of such data is very challenging, since it consists of time-varying measurements of many variables which are heterogeneous in nature and with possibly many missing values, recorded over extensive time periods. There is a need to introduce alternative intuitive strategies that contribute to experts acquiring further knowledge from the ionospheric scintillation data. Such challenges motivated a study on the applicability of visualization techniques to support tasks of identification of relevant attributes in the study of the behavior of phenomena described by multiple time-varying variables, of which the ionospheric scintillation is a good example. In particular, this thesis introduces a visual analytics framework, named TV-MV Analytics, that supports exploratory tasks on time-varying multivariate data and was developed following the requirements of experts on ionospheric scintillation from the Faculty of Science and Technology of UNESP at Presidente Prudente, Brazil. TV-MV Analytics provides an interactive visual exploration loop to analysts inspecting the behavior of multiple variables at different temporal scales, through temporal representations associated with clustering and multidimensional projection techniques. Analysts can also assess how different feature sub-spaces contribute to characterizing a certain behavior, where they may direct the analysis process and include their domain knowledge in the exploratory analysis. We also illustrate the application of TV-MV Analytics on multivariate time-varying data sets from three alternative application domains. Experimental results indicate the proposed solutions show good potential on assisting time-varying multivariate data mining tasks, since it reduces the effort required from experts to gain deeper insight into the historical behavior of the variables describing a phenomenon or domain. , Situação: Concluído; Natureza: Pesquisa. , Alunos envolvidos: Doutorado: (1) . , Integrantes: Aurea Rossy Soriano Vargas - Integrante / F. OLIVEIRA, MARIA CRISTINA - Coordenador / HAMANN, BERND - Integrante., Número de produções C, T & A: 2

• 2011 - 2013

  Alternative visual metaphors for layouts generated by multidimensional projections: a case study in visualization of music, Descrição: The layouts generated by multidimensional projection techniques can be the basis for different visualization metaphors that are applicable to various data types. There is much interest in investigating alternatives to the point cloud metaphor commonly used to present projection layouts. In this work, we investigated this problem, targeting the domain of music visualization. There are many dimensions involved in the perception and manipulation of music and therefore it is difficult to find an intuitive computer model to represent music. Our goal in this work was to investigate visual representations capable of conveying the musical structure of a song, as well as displaying a collection of songs so as to highlight their similarities. The proposed solution consists of an iconic representation for individual songs, that is associated with the spatial positioning of groups or collections of songs generated by a multidimensional projection technique that reflects their structural similarity. Both the projection and the icon require a feature vector representation of the music. The features are extracted from MIDI files, as the nature of the MIDI descriptions allows the identification of the relevant musical structures. These features provide the input for both the dissimilarity comparison and for constructing the music icon. The spatial layout is computed with the Least Square Projection (LSP) technique, and similarities are computed using the Dynamic Time Warping (DTW) distance. The icon provides a visual summary of the chord repetitions in a particular song. We describe the process of generating these visual representations, describe a system that implements such funcionalities and illustrate how they can support some exploratory tasks on music collections, identifying possible usage scenarios. , Situação: Concluído; Natureza: Pesquisa. , Alunos envolvidos: Doutorado: (1) . , Integrantes: Aurea Rossy Soriano Vargas - Integrante / F. OLIVEIRA, MARIA CRISTINA - Coordenador., Número de produções C, T & A: 2

• 2008 - 2008

  Generalized Wavelet Product Integral for Rendering Dynamic of Shiny Objects., Situação: Concluído; Natureza: Pesquisa. , Integrantes: Aurea Rossy Soriano Vargas - Coordenador.

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