{"id":1768,"date":"2025-10-21T00:06:22","date_gmt":"2025-10-21T00:06:22","guid":{"rendered":"https:\/\/eic.cefet-rj.br\/~dal\/?page_id=1768"},"modified":"2025-10-21T00:23:34","modified_gmt":"2025-10-21T00:23:34","slug":"publications","status":"publish","type":"page","link":"https:\/\/eic.cefet-rj.br\/~dal\/en\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<blockquote><p>Journals<\/p><\/blockquote>\n<div class=\"csl-bib-body\">[1] R. Salles, B. Lange, R. Akbarinia, F. Masseglia, E. Ogasawara, and E. Pacitti, \u201cScalable and accurate online multivariate anomaly detection,\u201d Information Systems, vol. 131, p. 102524, Jun. 2025, doi: 10.1016\/j.is.2025.102524.<br \/>\n[2] R. Salles, J. Lima, M. Reis, R. Coutinho, E. Pacitti, F. Masseglia, R. Akbarinia, C. Chen, J. Garibaldi, F. Porto, and E. Ogasawara, \u201cSoftED: Metrics for soft evaluation of time series event detection,\u201d Computers and Industrial Engineering, vol. 198. 2024. doi: 10.1016\/j.cie.2024.110728.<br \/>\n[3] F. Marques, L. Lignani, J. Quadros, M. Amorim, W. Viana, E. Ogasawara, and J. dos Santos, \u201cProBee: A Provenance-based Design for an Educational Game Analytics Model,\u201d Technology, Knowledge and Learning. 2024. doi: 10.1007\/s10758-024-09758-x.<br \/>\n[4] D. S. de Salles, C. Gea, C. E. Mello, L. Assis, R. Coutinho, E. Bezerra, and E. Ogasawara, \u201cMulti-Scale Event Detection in Financial Time Series,\u201d Computational Economics. 2024. doi: 10.1007\/s10614-024-10582-9.<br \/>\n[5] F. Carvalho, F. P. Junior, E. Ogasawara, L. Ferrari, and G. Guedes, \u201cEvaluation of the Brazilian Portuguese version of linguistic inquiry and word count 2015 (BP-LIWC2015),\u201d Language Resources and Evaluation, vol. 58, no. 1. pp. 203\u2013222, 2024. doi: 10.1007\/s10579-023-09647-2.<br \/>\n[6] J. Souza, C. Boccolini, L. Baroni, K. Belloze, E. Bezerra, M. Pedroso, R. F. S. Alves, and E. Ogasawara, \u201cEvaluation of statistical process control charts for infant mortality monitoring in Brazilian cities with different population sizes,\u201d BMC Research Notes, vol. 17, no. 1. 2024. doi: 10.1186\/s13104-024-06943-0.<br \/>\n[7] A. Mello, L. Giusti, T. Tavares, F. Alexandrino, G. Guedes, J. Soares, R. Barbastefano, F. Porto, D. Carvalho, and E. Ogasawara, \u201cD-AI2-M: Ethanol Production Forecasting in Brazil Using Data-Centric Artificial Intelligence Methodology,\u201d IEEE Latin America Transactions, vol. 22, no. 11, Art. no. 11, Oct. 2024.<br \/>\n[8] L. Baroni, L. Scoralick, A. Reis, K. Belloze, M. Pedroso, R. Alves, C. Boccolini, P. Boccolini, and E. Ogasawara, \u201cA contextual-compositional approach to discover associations between health determinants and health indicators for neonatal mortality rate monitoring in situations of anomalies,\u201d PLOS ONE, vol. 19, no. 12, p. e0310413, de dez. de 2024, doi: 10.1371\/journal.pone.0310413.<br \/>\n[9] F. P. G. de S\u00e1, R. C. de Coutinho, E. Ogasawara, D. Brand\u00e3o, and R. F. Toso, \u201cWind turbine fault detection: a semi-supervised learning approach with two different dimensionality reduction techniques,\u201d International Journal of Innovative Computing and Applications, vol. 14, no. 1\u20132. pp. 67\u201377, 2023. doi: 10.1504\/IJICA.2023.129359.<br \/>\n[10] P. Elias, H. de S. Campos, E. Ogasawara, and L. G. P. Murta, \u201cTowards accurate recommendations of merge conflicts resolution strategies,\u201d Information and Software Technology, vol. 164. 2023. doi: 10.1016\/j.infsof.2023.107332.<br \/>\n[11] C. Gea, L. Vereda, and E. Ogasawara, \u201cDetection of Uncertainty Events in the Brazilian Economic and Financial Time Series,\u201d Computational Economics. 2023. doi: 10.1007\/s10614-023-10483-3.<br \/>\n[12] A. Vasconcelos, J. Monsores, T. Almeida, L. Quadros, E. Ogasawara, and J. Quadros, \u201cApplying Gestalt approach as a method for teaching computer science practice in the classroom: A case study in primary schools in Brazil,\u201d Education and Information Technologies, vol. 28, no. 2. pp. 2383\u20132403, 2023. doi: 10.1007\/s10639-022-11278-z.<br \/>\n[13] R. Salles, E. Pacitti, E. Bezerra, F. Porto, and E. Ogasawara, \u201cTSPred: A framework for nonstationary time series prediction,\u201d Neurocomputing, vol. 467. pp. 197\u2013202, 2022. doi: 10.1016\/j.neucom.2021.09.067.<br \/>\n[14] F. Porto et al., \u201cMachine Learning Approaches to Extreme Weather Events Forecast in Urban Areas: Challenges and Initial Results,\u201d Supercomputing Frontiers and Innovations, vol. 9, no. 1. pp. 49\u201373, 2022. doi: 10.14529\/jsfi220104.<br \/>\n[15] B. dos Santos de Assis, E. Ogasawara, R. Barbastefano, and D. Carvalho, \u201cFrequent pattern mining augmented by social network parameters for measuring graduation and dropout time factors: A case study on a production engineering course,\u201d Socio-Economic Planning Sciences, vol. 81. 2022. doi: 10.1016\/j.seps.2021.101200.<br \/>\n[16] L. Giusti, L. Carvalho, A. T. Gomes, R. Coutinho, J. Soares, and E. Ogasawara, \u201cAnalyzing flight delay prediction under concept drift,\u201d Evolving Systems, vol. 13, no. 5. pp. 723\u2013736, 2022. doi: 10.1007\/s12530-021-09415-z.<br \/>\n[17] C. Teixeira, L. Fragoso, M. Mattoso, D. Carvalho, E. Bezerra, J. Soares, G. Amorim, and E. Ogasawara, \u201cA horizontal partitioning-based method for frequent pattern mining in transport timetable,\u201d Expert Systems, vol. 39, no. 2. 2022. doi: 10.1111\/exsy.12881.<br \/>\n[18] R. Castro, Y. M. Souto, E. Ogasawara, F. Porto, and E. Bezerra, \u201cSTConvS2S: Spatiotemporal Convolutional Sequence to Sequence Network for weather forecasting,\u201d Neurocomputing, vol. 426. pp. 285\u2013298, 2021. doi: 10.1016\/j.neucom.2020.09.060.<br \/>\n[19] L. Carvalho, A. Sternberg, L. Maia Gon\u00e7alves, A. Beatriz Cruz, J. A. Soares, D. Brand\u00e3o, D. Carvalho, and E. Ogasawara, \u201cOn the relevance of data science for flight delay research: a systematic review,\u201d Transport Reviews, vol. 41, no. 4. pp. 499\u2013528, 2021. doi: 10.1080\/01441647.2020.1861123.<br \/>\n[20] L. Baroni et al., \u201cNeonatal mortality rates in Brazilian municipalities: from 1996 to 2017,\u201d BMC Research Notes, vol. 14, no. 1. 2021. doi: 10.1186\/s13104-020-05441-3.<br \/>\n[21] L. Escobar, R. Salles, J. Lima, C. Gea, L. Baroni, A. Ziviani, P. Pires, F. Delicato, R. Coutinho, L. Assis, and E. Ogasawara, \u201cEvaluating Temporal Bias in Time Series Event Detection Methods,\u201d Journal of Information and Data Management, vol. 12, no. 3, Art. no. 3, Oct. 2021, doi: 10.5753\/jidm.2021.1968.<br \/>\n[22] B. Paix\u00e3o, L. Baroni, M. Pedroso, R. Salles, L. Escobar, C. de Sousa, R. de Freitas Saldanha, J. Soares, R. Coutinho, F. Porto, and E. Ogasawara, \u201cEstimation of COVID-19 Under-Reporting in the Brazilian States Through SARI,\u201d New Generation Computing, vol. 39, no. 3\u20134. pp. 623\u2013645, 2021. doi: 10.1007\/s00354-021-00125-3.<br \/>\n[23] J. Cardoso, D. Caetano, R. Abreu, J. Quadros, J. D. Santos, E. Ogasawara, and L. Lignani, \u201cSupporting the Learning of Evolution Theory Using an Educational Simulator,\u201d IEEE Transactions on Learning Technologies, vol. 13, no. 2. pp. 417\u2013424, 2020. doi: 10.1109\/TLT.2019.2911613.<br \/>\n[24] H. Borges, M. Dutra, A. Bazaz, R. Coutinho, F. Perosi, F. Porto, F. Masseglia, E. Pacitti, and E. Ogasawara, \u201cSpatial-time motifs discovery,\u201d Intelligent Data Analysis, vol. 24, no. 5. pp. 1121\u20131140, 2020. doi: 10.3233\/IDA-194759.<br \/>\n[25] F. Paschoal J\u00fanior, G. V. S. Ribeiro, L. M. de A. Daquer, R. C. Mauro, E. S. Ogasawara, and N. F. F. Ebecken, \u201cPhysical activity level of facebook users; [N\u00edvel de atividade f\u00edsica dos usu\u00e1rios do facebook]; [Nivel de actividad f\u00edsica de los usuarios de facebook],\u201d Revista Brasileira de Medicina do Esporte, vol. 26, no. 6. pp. 517\u2013522, 2020. doi: 10.1590\/1517-869220202606179014.<br \/>\n[26] R. Guimaraes Rodrigues, K. Tavares Rodrigues, R. Reis Gomes, L. Ferrari, E. Ogasawara, and G. Paiva Guedes, \u201cBRAPT: A New Metric for Translation Evaluation Based on Psycholinguistic Perspectives,\u201d IEEE Latin America Transactions, vol. 18, no. 7. pp. 1264\u20131271, 2020. doi: 10.1109\/TLA.2020.9099768.<br \/>\n[27] L. Baroni, M. Pedroso, C. Barcellos, R. Salles, S. Salles, B. Paix\u00e3o, A. Chrispino, G. Guedes, and E. Ogasawara, \u201cAn integrated dataset of malaria notifications in the Legal Amazon,\u201d BMC Research Notes, vol. 13, no. 1. 2020. doi: 10.1186\/s13104-020-05109-y.<br \/>\n[28] L. Baroni, R. Salles, S. Salles, G. Guedes, F. Porto, E. Bezerra, C. Barcellos, M. Pedroso, and E. Ogasawara, \u201cAn analysis of malaria in the Brazilian Legal Amazon using divergent association rules,\u201d Journal of Biomedical Informatics, vol. 108. 2020. doi: 10.1016\/j.jbi.2020.103512.<br \/>\n[29] R. Salles, K. Belloze, F. Porto, P. H. Gonzalez, and E. Ogasawara, \u201cNonstationary time series transformation methods: An experimental review,\u201d Knowledge-Based Systems, vol. 164. pp. 274\u2013291, 2019. doi: 10.1016\/j.knosys.2018.10.041.<br \/>\n[30] A. Marinho, D. de Oliveira, E. Ogasawara, V. Silva, K. Oca\u00f1a, L. Murta, V. Braganholo, and M. Mattoso, \u201cDeriving scientific workflows from algebraic experiment lines: A practical approach,\u201d Future Generation Computer Systems, vol. 68. pp. 111\u2013127, 2017. doi: 10.1016\/j.future.2016.08.016.<br \/>\n[31] R. Salles, P. Mattos, A.-M. D. Iorgulescu, E. Bezerra, L. Lima, and E. Ogasawara, \u201cEvaluating temporal aggregation for predicting the sea surface temperature of the Atlantic Ocean,\u201d Ecological Informatics, vol. 36. pp. 94\u2013105, 2016. doi: 10.1016\/j.ecoinf.2016.10.004.<br \/>\n[32] G. P. Guedes, E. Ogasawara, E. Bezerra, and G. Xexeo, \u201cDiscovering top-k non-redundant clusterings in attributed graphs,\u201d Neurocomputing, vol. 210. pp. 45\u201354, 2016. doi: 10.1016\/j.neucom.2015.10.145.<br \/>\n[33] A. Sternberg, D. Carvalho, L. Murta, J. Soares, and E. Ogasawara, \u201cAn analysis of Brazilian flight delays based on frequent patterns,\u201d Transportation Research Part E: Logistics and Transportation Review, vol. 95. pp. 282\u2013298, 2016. doi: 10.1016\/j.tre.2016.09.013.<br \/>\n[34] L. Pimentel, K. Belloze, J. Soares, E. Ogasawara, and R. Mauro, \u201cUma ferramenta para planejamento de estudos para concursos,\u201d Revista Brasileira de Computa\u00e7\u00e3o Aplicada, vol. 7, no. 3, Art. no. 3, Oct. 2015, doi: 10.5335\/rbca.2015.4506.<br \/>\n[35] M. Mattoso, J. Dias, K. A. C. S. Oca\u00f1a, E. Ogasawara, F. Costa, F. Horta, V. Silva, and D. De Oliveira, \u201cDynamic steering of HPC scientific workflows: A survey,\u201d Future Generation Computer Systems, vol. 46. pp. 100\u2013113, 2015. doi: 10.1016\/j.future.2014.11.017.<br \/>\n[36] J. R. de T. Quadros, D. Oliveira, A. Queiroz, E. Ogasawara, and C. Schocair, \u201cTowards a UML-based Reference Model for Blended Learning,\u201d International Journal of Recent Contributions from Engineering, Science &amp; IT (iJES), vol. 2, no. 3, Art. no. 3, Aug. 2014, doi: 10.3991\/ijes.v2i3.3818.<br \/>\n[37] L. Mosquera, E. Ogasawara, R. Barbastefano, and E. Bezerra, \u201cProposta de Modelo de Avalia\u00e7\u00e3o de Formas de Ado\u00e7\u00e3o e Acompanhamento de Ferramentas de Redes Sociais Corporativas,\u201d Sistemas &amp; Gest\u00e3o, vol. 9, no. 4, Art. no. 4, Dec. 2014, doi: 10.7177\/sg.2014.V9.N4.A9.<br \/>\n[38] G. P. G. e Silva, E. Bezerra, E. Ogasawara, and G. Xexeo, \u201cMAM: M\u00e9todo para Agrupamentos M\u00faltiplos em Redes Sociais Online Baseado em Emo\u00e7\u00f5es, Personalidades e Textos,\u201d iSys &#8211; Brazilian Journal of Information Systems, vol. 7, no. 3, Art. no. 3, Nov. 2014, doi: 10.5753\/isys.2014.256.<br \/>\n[39] D. De Oliveira, K. A. C. S. Oca\u00f1a, E. Ogasawara, J. Dias, J. Gon\u00e7alves, F. Bai\u00e3o, and M. Mattoso, \u201cPerformance evaluation of parallel strategies in public clouds: A study with phylogenomic workflows,\u201d Future Generation Computer Systems, vol. 29, no. 7. pp. 1816\u20131825, 2013. doi: 10.1016\/j.future.2012.12.019.<br \/>\n[40] J. Gon\u00e7alves, D. de Oliveira, K. Oca\u00f1a, E. Ogasawara, J. Dias, and M. Mattoso, \u201cPerformance Analysis of Data Filtering in Scientific Workflows,\u201d Journal of Information and Data Management, vol. 4, no. 1, Art. no. 1, Jun. 2013, doi: 10.5753\/jidm.2013.1466.<br \/>\n[41] K. A. C. S. Oca\u00f1a, D. De Oliveira, J. Dias, E. Ogasawara, and M. Mattoso, \u201cDesigning a parallel cloud based comparative genomics workflow to improve phylogenetic analyses,\u201d Future Generation Computer Systems, vol. 29, no. 8. pp. 2205\u20132219, 2013. doi: 10.1016\/j.future.2013.04.005.<br \/>\n[42] J. R. de T. Quadros, R. Castaneda, M. Amorim, G. Herzog, L. Carneiro, K. Menezes, M. Pinheiro, D. de Oliveira, and E. Ogasawara, \u201cConstru\u00e7\u00e3o de ambiente para desenvolvimento de jogos educacionais baseados em interface de gestos,\u201d Revista Brasileira de Computa\u00e7\u00e3o Aplicada, vol. 5, no. 2, pp. 110\u2013119, Sep. 19, 2013.<br \/>\n[43] E. Ogasawara, J. Dias, V. Silva, F. Chirigati, D. De Oliveira, F. Porto, P. Valduriez, and M. Mattoso, \u201cChiron: A parallel engine for algebraic scientific workflows,\u201d Concurrency and Computation: Practice and Experience, vol. 25, no. 16. pp. 2327\u20132341, 2013. doi: 10.1002\/cpe.3032.<br \/>\n[44] E. Ogasawara, D. De Oliveira, F. Paschoal Jr., R. Castaneda, M. Amorim, R. Mauro, J. Soares, J. Quadros, and E. Bezerra, \u201cA forecasting method for fertilizers consumption in Brazil,\u201d International Journal of Agricultural and Environmental Information Systems, vol. 4, no. 2. pp. 23\u201336, 2013. doi: 10.4018\/jaeis.2013040103.<br \/>\n[45] G. Guerra, F. A. Rochinha, R. Elias, D. de Oliveira, E. Ogasawara, J. F. Dias, M. Mattoso, and A. L. G. A. Coutinho, \u201cUncertainty Quantification in Computational Predictive Models for Fluid Dynamics Using a Workflow Management Engine,\u201d IJUQ, vol. 2, no. 1, 2012, doi: 10.1615\/Int.J.UncertaintyQuantification.v2.i1.50.<br \/>\n[46] A. Marinho, L. Murta, C. Werner, V. Braganholo, S. M. S. D. Cruz, E. Ogasawara, and M. Mattoso, \u201cProvManager: A provenance management system for scientific workflows,\u201d Concurrency and Computation: Practice and Experience, vol. 24, no. 13. pp. 1513\u20131530, 2012. doi: 10.1002\/cpe.1870.<br \/>\n[47] D. de Oliveira, E. Ogasawara, J. Dias, F. Bai\u00e3o, and M. Mattoso, \u201cOntology-based Semi-automatic Workflow Composition,\u201d Journal of Information and Data Management, vol. 3, no. 1, Art. no. 1, Jul. 2012, doi: 10.5753\/jidm.2012.1434.<br \/>\n[48] D. De Oliveira, E. Ogasawara, K. Oca\u00f1a, F. Bai\u00e3o, and M. Mattoso, \u201cAn adaptive parallel execution strategy for cloud-based scientific workflows,\u201d Concurrency and Computation: Practice and Experience, vol. 24, no. 13. pp. 1531\u20131550, 2012. doi: 10.1002\/cpe.1880.<br \/>\n[49] M. C. Garbin, S. F. do Amaral, C. O. S. Mendes, E. Ogasawara, and J. M. de S. Rocha, \u201cAdaptation of the Moodle for Application in Distance Education Course at the State University of Campinas,\u201d Procedia &#8211; Social and Behavioral Sciences, vol. 46, pp. 2514\u20132518, Jan. 2012, doi: 10.1016\/j.sbspro.2012.05.513.<br \/>\n[50] V. Silva, F. Chirigati, K. Maia, E. Ogasawara, D. Oliveira, V. Braganholo, and M. Mattoso, \u201cSimilarity-based workflow clustering,\u201d Journal of Computational Interdisciplinary Sciences, vol. 2, no. 1, 2011.<br \/>\n[51] F. Coutinho, E. Ogasawara, D. De Oliveira, V. Braganholo, A. A. B. Lima, A. M. R. D\u00e1vila, and M. Mattoso, \u201cMany task computing for orthologous genes identification in protozoan genomes using Hydra,\u201d Concurrency and Computation: Practice and Experience, vol. 23, no. 17. pp. 2326\u20132337, 2011. doi: 10.1002\/cpe.1786.<br \/>\n[52] E. Ogasawara, D. de Oliveira, P. Valduriez, J. Dias, F. Porto, and M. Mattoso, \u201cAn algebraic approach for data-centric scientific workflows,\u201d Proceedings of the VLDB Endowment, vol. 4, no. 12. pp. 1328\u20131339, 2011.<br \/>\n[53] M. Mattoso, C. Werner, G. H. Travassos, V. Braganholo, E. Ogasawara, D. De Oliveira, S. M. S. Da Cruz, W. Martinho, and L. Murta, \u201cTowards supporting the life cycle of large scale scientific experiments,\u201d International Journal of Business Process Integration and Management, vol. 5, no. 1. pp. 79\u201392, 2010. doi: 10.1504\/IJBPIM.2010.033176.<\/div>\n<blockquote><p>Conferences<\/p><\/blockquote>\n<div class=\"csl-bib-body\">[1] A. Brayner, A. P. L. de Carvalho, D. D. A. Ruiz, and E. Ogasawara, \u201cUm Farol para Cria\u00e7\u00e3o e Avalia\u00e7\u00e3o de Cursos de Ci\u00eancia de Dados: Os Referenciais Curriculares da SBC,\u201d in Simp\u00f3sio Brasileiro de Educa\u00e7\u00e3o em Computa\u00e7\u00e3o (EDUCOMP), SBC, Apr. 2024, pp. 266\u2013272. doi: 10.5753\/educomp.2024.237484.<br \/>\n[2] R. Garcia, E. Ogasawara, J. Soares, A. de Souza, R. Sobrino, and E. Bezerra, \u201cUm Experimento de Engenharia de Features para Gera\u00e7\u00e3o de Modelos Preditivos para Casos de Dengue,\u201d in Brazilian e-Science Workshop (BreSci), SBC, Oct. 2024, pp. 151\u2013158. doi: 10.5753\/bresci.2024.243949.<br \/>\n[3] J. Souza, E. P\u00e3ixao, F. Fraga, L. Baroni, R. F. S. Alves, K. Belloze, J. Dos Santos, E. Bezerra, F. Porto, and E. Ogasawara, \u201cREMD: A Novel Hybrid Anomaly Detection Method Based on EMD and ARIMA,\u201d Proceedings of the International Joint Conference on Neural Networks. 2024. doi: 10.1109\/IJCNN60899.2024.10651192.<br \/>\n[4] L. Calmon, R. Ferro, C. Pereira, C. Souza, L. Giusti, G. Amorim, and E. Ogasawara, \u201cPrevis\u00e3o de Sucesso de Atletas Jovens de Futebol usando Integra\u00e7\u00e3o de diferentes Base de Dados,\u201d in Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2024, pp. 855\u2013861. doi: 10.5753\/sbbd.2024.243187.<br \/>\n[5] A. Mello, D. Carvalho, and E. Ogasawara, \u201cPredi\u00e7\u00e3o da Produ\u00e7\u00e3o de Etanol nos Estados Brasileiros,\u201d in Brazilian e-Science Workshop (BreSci), SBC, Oct. 2024, pp. 120\u2013127. doi: 10.5753\/bresci.2024.243818.<br \/>\n[6] J. Lima, L. G. Tavares, E. Pacitti, J. E. Ferreira, I. Santos, I. G. Siqueira, D. Carvalho, F. Porto, R. Coutinho, and E. Ogasawara, \u201cOnline Event Detection in Streaming Time Series: Novel Metrics and Practical Insights,\u201d Proceedings of the International Joint Conference on Neural Networks. pp. 1\u20138, 2024. doi: 10.1109\/IJCNN60899.2024.10650809.<br \/>\n[7] M. Reis, R. Salles, G. Xex\u00e9o, R. Coutinho, and E. Ogasawara, \u201cMatching Detections to Events in Time Series,\u201d in Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2024, pp. 785\u2013791. doi: 10.5753\/sbbd.2024.243275.<br \/>\n[8] A. Fonseca, R. Goldschimidt, E. Ogasawara, M. Ferro, F. Porto, and E. Bezerra, \u201cInterpola\u00e7\u00e3o e Previs\u00e3o de Precipita\u00e7\u00e3o por Redes Neurais Convolucionais para Grafos,\u201d in Brazilian Symposium on Multimedia and the Web (WebMedia), SBC, Oct. 2024, pp. 395\u2013399. doi: 10.5753\/webmedia.2024.242049.<br \/>\n[9] M. S. Moura, L. Baroni, E. Ogasawara, and D. S. Mendon\u00e7a, \u201cHD Pump: A Hybrid Detection Approach for Pump-and-Dump Schemes in Cryptocurrency Exchanges,\u201d in Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2024, pp. 757\u2013763. doi: 10.5753\/sbbd.2024.243293.<br \/>\n[10] N. Tito, B. Paix\u00e3o, L. G. Tavares, E. Ogasawara, and G. F. Amorim, \u201cDiferenciando Perfis de Corredores por Meio de Pontos de Mudan\u00e7a nos Treinos,\u201d in Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2024, pp. 834\u2013840. doi: 10.5753\/sbbd.2024.243205.<br \/>\n[11] E. P. Silva, H. Balbi, E. Pacitti, F. Porto, J. Santos, and E. Ogasawara, \u201cCutoff Frequency Adjustment for FFT-Based Anomaly Detectors,\u201d in Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2024, pp. 708\u2013714. doi: 10.5753\/sbbd.2024.243319.<br \/>\n[12] F. Santos, L. Giusti, D. Carvalho, E. Ogasawara, and J. Soares, \u201cAvalia\u00e7\u00e3o de Desvios de Conceitos Reais e Virtuais nos Atrasos de Voos em S\u00e3o Paulo nos Per\u00edodos Pr\u00e9, Intra e P\u00f3s-Pandemia,\u201d in Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2024, pp. 827\u2013833. doi: 10.5753\/sbbd.2024.243111.<br \/>\n[13] F. Alexandrino, C. Pacheco, D. Carvalho, and E. Ogasawara, \u201cAumento de dados e suaviza\u00e7\u00e3o integrada para predi\u00e7\u00e3o de s\u00e9ries temporais baseada em aprendizado de m\u00e1quina,\u201d in Brazilian e-Science Workshop (BreSci), SBC, Oct. 2024, pp. 32\u201339. doi: 10.5753\/bresci.2024.244100.<br \/>\n[14] B. O. Barbosa, L. A. B. Marinho, M. D. Santos, F. Alexandrino, R. Coutinho, U. de Paula, D. Carvalho, and E. Ogasawara, \u201cAn\u00e1lise de Modelos Baseados em WiSARD para Classifica\u00e7\u00e3o de Trajet\u00f3rias de \u00d4nibus no Contexto da Mobilidade Urbana,\u201d in Brazilian e-Science Workshop (BreSci), SBC, Oct. 2024, pp. 1\u20137. doi: 10.5753\/bresci.2024.243296.<br \/>\n[15] V. K. de Almeida et al., \u201cA Digital Twin System for Oil And Gas Industry: A Use Case on Mooring Lines Integrity Monitoring,\u201d in Proceedings of the ACM\/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, in MODELS Companion \u201924. New York, NY, USA: Association for Computing Machinery, Outubro 2024, pp. 322\u2013331. doi: 10.1145\/3652620.3688244.<br \/>\n[16] H. Borges, A. Castro, R. Coutinho, F. Porto, E. Pacitti, and E. Ogasawara, \u201cSTMotif Explorer: A Tool for Spatiotemporal Motif Analysis,\u201d in Anais Estendidos do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Sep. 2023, pp. 114\u2013119. doi: 10.5753\/sbbd_estendido.2023.233371.<br \/>\n[17] A. Castro, H. Borges, C. Souza, J. Rodrigues, F. Porto, E. Pacitti, R. Coutinho, and E. Ogasawara, \u201cGSTSM Package: Finding Frequent Sequences in Constrained Space and Time,\u201d in BDA 2023\u202f: 39\u00e8me Conf\u00e9rence sur la Gestion de Donn\u00e9es \u2013 Principes, Technologies et Applications, BDA, Sep. 2023, pp. 1\u20132.<br \/>\n[18] B. Capistrano, L. Chen, M. Ribeiro, C. Pacheco, D. Lobosco, J. Quadros, M. I. Barreto, and E. Ogasawara, \u201cDesafios na Predi\u00e7\u00e3o do Consumo de Pesticidas em Escala Global Usando Aprendizado de M\u00e1quina,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Sep. 2023, pp. 33\u201338. doi: 10.5753\/bresci.2023.233831.<br \/>\n[19] M. Pedroso et al., \u201cData Science Platform Applied to Health in Contribution to the Brazilian Unified Health System,\u201d 2nd International Workshop on Data Ecosystems (DEco), vol. 3462. 2023.<br \/>\n[20] L. Oliveira, L. S. de Assis, E. Ogasawara, and J. Rosa, \u201cAloca\u00e7\u00e3o \u00d3tima de Equipamentos na Completa\u00e7\u00e3o de Po\u00e7os de Petr\u00f3leo Submarinos: Uma Abordagem Espa\u00e7o-Temporal por Programa\u00e7\u00e3o Matem\u00e1tica,\u201d in Anais do LV Simp\u00f3sio Brasileiro de Pesquisa Operacional, S\u00e3o Jos\u00e9 dos Campos, SP: Galo\u00e1, 2023, pp. 1\u201312. doi: 10.59254\/sbpo-2023-175159.<br \/>\n[21] L. Iza\u00fa, M. Fortes, V. Ribeiro, C. Marques, C. Oliveira, E. Bezerra, F. Porto, R. Salles, and E. Ogasawara, \u201cTowards Robust Cluster-Based Hyperparameter Optimization,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Sep. 2022, pp. 439\u2013444. doi: 10.5753\/sbbd.2022.224330.<br \/>\n[22] M. Ferro, E. Bezerra, E. Ogasawara, N. Moraes, and F. Porto, \u201cTowards a Definition for Extreme Weather Events in Rio de Janeiro City,\u201d in Anais Estendidos do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Sep. 2022, pp. 181\u2013186. doi: 10.5753\/sbbd_estendido.2022.21862.<br \/>\n[23] J. Lima, R. Salles, L. Escobar, C. G\u00e9a, P. A. Fernandes, E. Pacitti, F. Porto, R. Coutinho, and E. Ogasawara, \u201cTowards a cloud-based framework for online and integrated event detection,\u201d in Anais Estendidos do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Sep. 2022, pp. 199\u2013202. doi: 10.5753\/sbbd_estendido.2022.21865.<br \/>\n[24] R. B. de Castro, V. C. Monteiro, R. Coutinho, H. Borges, and E. Ogasawara, \u201cIdentification of the North Brazil Current through spatial motifs in fixed time slices,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Jul. 2022, pp. 17\u201324. doi: 10.5753\/bresci.2022.222622.<br \/>\n[25] J. Lima, R. Salles, F. Porto, R. Coutinho, P. Alpis, L. Escobar, E. Pacitti, and E. Ogasawara, \u201cForward and Backward Inertial Anomaly Detector: A Novel Time Series Event Detection Method,\u201d in 2022 International Joint Conference on Neural Networks (IJCNN), Jul. 2022, pp. 1\u20138. doi: 10.1109\/IJCNN55064.2022.9892088.<br \/>\n[26] C. Pacheco, M. Guimaraes, E. Bezerra, D. Lobosco, J. Soares, P. H. Gonz\u00e1lez, A. Andrade, C. G. De Souza, and E. Ogasawara, \u201cExploring Data Preprocessing and Machine Learning Methods for Forecasting Worldwide Fertilizers Consumption,\u201d Proceedings of the International Joint Conference on Neural Networks, vol. 2022-July. 2022. doi: 10.1109\/IJCNN55064.2022.9892325.<br \/>\n[27] A. J. M. da Fonseca, F. Porto, M. Ferro, E. Ogasawara, and E. Bezerra, \u201cAnalysis of precipitation data in Rio de Janeiro city using Extreme Value Theory,\u201d in Anais Estendidos do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Sep. 2022, pp. 193\u2013198. doi: 10.5753\/sbbd_estendido.2022.21864.<br \/>\n[28] R. Zorrilla, E. Ogasawara, P. Valduriez, and F. Porto, \u201cA Data-Driven Model Selection Approach to Spatio-Temporal Prediction,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Sep. 2022, pp. 1\u201312. doi: 10.5753\/sbbd.2022.224638.<br \/>\n[29] K. Buckles, E. Bezerra, E. Ogasawara, and M. Guimaraes, \u201cWrapper algorithm for choosing machine learning functions and methods in SSAS,\u201d in J. Comput. Sci. Coll., Oct. 2021, pp. 92\u2013100.<br \/>\n[30] C. Barros, R. Salles, E. Ogasawara, G. Guizzardi, and F. Porto, \u201cRequirements for an ontology of digital twins,\u201d CEUR Workshop Proceedings, vol. 2941. 2021.<br \/>\n[31] E. Ogasawara, R. Salles, L. Escobar, L. Baroni, J. Lima, and F. Porto, \u201cOnline event detection for sensor data,\u201d in XLII Ibero-Latin American Congress on Computational Methods in Engineering, Rio de Janeiro, RJ, 2021, pp. 1\u20137.<br \/>\n[32] T. Moeda, M. Ferro, E. Ogasawara, and F. Porto, \u201cMethod for Treating Anomalies in Multivariate Time Series,\u201d in XLII Ibero-Latin American Congress on Computational Methods in Engineering, 2021.<br \/>\n[33] C. Teixeira, L. Giusti, J. Soares, J. dos Santos, G. Amorim, and E. Ogasawara, \u201cIntegrated Dataset of Brazilian Flights,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Jul. 2021, pp. 89\u201396. doi: 10.5753\/bresci.2021.15793.<br \/>\n[34] A. Castro, H. Borges, R. Campisano, E. Pacitti, F. Porto, R. Coutinho, and E. Ogasawara, \u201cGeneraliza\u00e7\u00e3o de Minera\u00e7\u00e3o de Sequ\u00eancias Restritas no Espa\u00e7o e no Tempo,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2021, pp. 313\u2013318. doi: 10.5753\/sbbd.2021.17891.<br \/>\n[35] M. Mello, V. Belloni, F. Vasconcellos, J. Soares, E. Ogasawara, and L. Giusti, \u201cFun\u00e7\u00f5es Executivas e Idade Relativa como Preditores de Sucesso no Futebol,\u201d in Anais da Escola Regional de Inform\u00e1tica do Rio de Janeiro (ERI-RJ), SBC, Nov. 2021, pp. 111\u2013118. doi: 10.5753\/eri-rj.2021.18782.<br \/>\n[36] R. Pereira, Y. Souto, A. Chaves, R. Zorilla, B. Tsan, F. Rusu, E. Ogasawara, A. Ziviani, and F. Porto, \u201cDJEnsemble: A Cost-Based Selection and Allocation of a Disjoint Ensemble of Spatio-Temporal Models,\u201d ACM International Conference Proceeding Series. pp. 226\u2013231, 2021. doi: 10.1145\/3468791.3468806.<br \/>\n[37] R. Campos, H. Benini, J. dos Santos, E. Ogasawara, and F. Marques, \u201cClassifica\u00e7\u00e3o da Avalia\u00e7\u00e3o de Imers\u00e3o em Aplica\u00e7\u00f5es Multissensoriais,\u201d in Anais da Escola Regional de Inform\u00e1tica do Rio de Janeiro (ERI-RJ), SBC, Nov. 2021, pp. 127\u2013130. doi: 10.5753\/eri-rj.2021.18785.<br \/>\n[38] R. P. Salles, E. Ogasawara, and P. Gonz\u00e1lez, \u201cBenchmarking Nonstationary Time Series Prediction,\u201d in Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2021, pp. 177\u2013182. doi: 10.5753\/sbbd_estendido.2021.18182.<br \/>\n[39] G. Souto, B. Capistrano, M. Matias, J. Soares, E. Ogasawara, and L. Giusti, \u201cAvalia\u00e7\u00e3o dos diferentes tipos de redes LSTM para predi\u00e7\u00e3o de a\u00e7\u00f5es na bolsa de valores,\u201d in Anais da Escola Regional de Inform\u00e1tica do Rio de Janeiro (ERI-RJ), SBC, Nov. 2021, pp. 65\u201371. doi: 10.5753\/eri-rj.2021.18776.<br \/>\n[40] C. Gea, J. Lima, E. Bezerra, and E. Ogasawara, \u201cAn\u00e1lise de m\u00e9todos de tratamento de outliers para predi\u00e7\u00e3o dos retornos de \u00edndices de a\u00e7\u00f5es negociados em bolsa,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Oct. 2021, pp. 277\u2013282. doi: 10.5753\/sbbd.2021.17885.<br \/>\n[41] M. B. Ferreira, M. Amorim, E. Ogasawara, and R. Barbastefano, \u201cA interdisciplinaridade no desempenho da nota de matem\u00e1tica: um olhar para evolu\u00e7\u00e3o do processo de ensino por meio de modelos regressivos,\u201d in Anais da Escola Regional de Inform\u00e1tica do Rio de Janeiro (ERI-RJ), SBC, Nov. 2021, pp. 41\u201348. doi: 10.5753\/eri-rj.2021.18773.<br \/>\n[42] F. P. G. De Sa, D. N. Brandao, E. Ogasawara, R. D. C. Coutinho, and R. F. Toso, \u201cWind Turbine Fault Detection: A Semi-Supervised Learning Approach with Automatic Evolutionary Feature Selection,\u201d International Conference on Systems, Signals, and Image Processing, vol. 2020-July. pp. 323\u2013328, 2020. doi: 10.1109\/IWSSIP48289.2020.9145244.<br \/>\n[43] A. Andrade, R. Salles, F. Carvalho, E. B. da Silva, J. Soares, C. Souza, P. H. Gonzalez, and E. Ogasawara, \u201cUso de ci\u00eancia de dados para predi\u00e7\u00e3o do consumo de fertilizantes no Brasil,\u201d in Brazilian e-Science Workshop (BreSci), SBC, Jun. 2020, pp. 9\u201316. doi: 10.5753\/bresci.2020.11176.<br \/>\n[44] R. Salles, L. Escobar, L. Baroni, R. Zorrilla, A. Ziviani, V. Kreischer, F. Delicato, P. F. Pires, L. Maia, R. Coutinho, L. Assis, and E. Ogasawara, \u201cHarbinger: Um framework para integra\u00e7\u00e3o e an\u00e1lise de m\u00e9todos de detec\u00e7\u00e3o de eventos em s\u00e9ries temporais,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Sep. 2020, pp. 73\u201384. doi: 10.5753\/sbbd.2020.13626.<br \/>\n[45] J. Fabian, A. Gomes, and E. Ogasawara, \u201cEstimating the execution time of fully-online multiscale numerical simulations,\u201d in Anais do Simp\u00f3sio em Sistemas Computacionais de Alto Desempenho (WSCAD), SBC, Oct. 2020, pp. 191\u2013202. doi: 10.5753\/wscad.2020.14069.<br \/>\n[46] A. Ronald, R. Salles, K. Belloze, D. Pastore, and E. Ogasawara, \u201cModelo Autorregressivo de Integra\u00e7\u00e3o Adaptativa,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Nov. 2019, pp. 175\u2013180. doi: 10.5753\/sbbd.2019.8819.<br \/>\n[47] F. Carvalho, L. F. Dos Santos, H. Borges, E. Ogasawara, and G. P. Guedes, \u201cDiscovering patterns in sentimental analysis,\u201d Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, WebMedia 2019. pp. 329\u2013332, 2019. doi: 10.1145\/3323503.3361683.<br \/>\n[48] L. R. Baroni, B. Paix\u00e3o, A. Chrispino, G. Guedes, C. Barcellos, M. Pedroso, and E. Ogasawara, \u201cAn\u00e1lise Explorat\u00f3ria da Mal\u00e1ria na Amaz\u00f4nia Brasileira por Meio da Plataforma de Ci\u00eancia de Dados aplicada \u00e0 Sa\u00fade,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Jun. 2019. doi: 10.5753\/bresci.2019.10025.<br \/>\n[49] D. Oliveira, C. M. Abreu, E. Ogasawara, E. Bezerra, and L. de Lima, \u201cA Science Gateway to Support Research in Spectral Graph Theory,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), SBC, Nov. 2019, pp. 217\u2013222. doi: 10.5753\/sbbd.2019.8826.<br \/>\n[50] D. N. R. da Silva et al., \u201cA conceptual vision toward the management of machine learning models,\u201d CEUR Workshop Proceedings, vol. 2469. pp. 15\u201327, 2019.<br \/>\n[51] P. Valduriez et al., \u201cScientific data analysis using data-intensive scalable computing: The SciDISC project,\u201d CEUR Workshop Proceedings, vol. 2170. pp. 1\u20138, 2018.<br \/>\n[52] J. A. Ferreira, F. Porto, R. Coutinho, and E. Ogasawara, \u201cRumo \u00e0 Otimiza\u00e7\u00e3o de Operadores sobre UDF no Spark,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Jul. 2018. doi: 10.5753\/bresci.2018.3280.<br \/>\n[53] J. Ferreira, J. Soares, F. Porto, E. Pacitti, R. Coutinho, and E. Ogasawara, \u201cRumo \u00e0 Integra\u00e7\u00e3o da \u00c1lgebra de Workflows ao Processamento de Consultas Relacionais,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 2018.<br \/>\n[54] F. Porto, A. Krone-Martins, J. N. Rittmeyer, P. Valduriez, E. Ogasawara, and D. Shasha, \u201cPoint pattern search in big data,\u201d ACM International Conference Proceeding Series. 2018. doi: 10.1145\/3221269.3221294.<br \/>\n[55] P. Chaves, L. Paschoal, T. Velasco, T. Bento, J. Brand\u00e3o, C. Schocair, J. Quadros, T. Oliveira, and E. Ogasawara, \u201cOrthographic educational game for Portuguese language countries,\u201d CSEDU 2018 &#8211; Proceedings of the 10th International Conference on Computer Supported Education, vol. 2. pp. 432\u2013440, 2018. doi: 10.5220\/0006757504320440.<br \/>\n[56] L. Moreira, C. Dantas, L. Oliveira, J. Soares, and E. Ogasawara, \u201cOn Evaluating Data Preprocessing Methods for Machine Learning Models for Flight Delays,\u201d Proceedings of the International Joint Conference on Neural Networks, vol. 2018-July. 2018. doi: 10.1109\/IJCNN.2018.8489294.<br \/>\n[57] L. Carvalho, L. Assis, L. Lima, E. Bezerra, G. Guedes, A. Ziviani, F. Porto, R. Barbastefano, and E. Ogasawara, \u201cEvaluating the complementarity of communication tools for learning platforms,\u201d CSEDU 2018 &#8211; Proceedings of the 10th International Conference on Computer Supported Education, vol. 2. pp. 142\u2013153, 2018. doi: 10.5220\/0006798701420153.<br \/>\n[58] R. Campisano, H. Borges, F. Porto, F. Perosi, E. Pacitti, F. Masseglia, and E. Ogasawara, \u201cDiscovering tight space-time sequences,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 11031 LNCS. pp. 247\u2013257, 2018. doi: 10.1007\/978-3-319-98539-8_19.<br \/>\n[59] A. B. Cruz, J. Ferreira, D. Carvalho, E. Mendes, E. Pacitti, R. Coutinho, F. Porto, and E. Ogasawara, \u201cDetec\u00e7\u00e3o de anomalias frequentes no transporte rodovi\u00e1rio urbano,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 2018.<br \/>\n[60] C. Monteiro, E. Ogasawara, L. Goncalves, and J. R. De Toledo Quadros, \u201cControl and security system for classroom access based on facial recognition,\u201d Proceedings &#8211; 2018 44th Latin American Computing Conference, CLEI 2018. pp. 654\u2013661, 2018. doi: 10.1109\/CLEI.2018.00084.<br \/>\n[61] F. Porto, A. Khatibi, J. G. Rittmeyer, E. Ogasawara, P. Valduriez, and D. Shasha, \u201cConstellation Queries over Big Data,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 2018.<br \/>\n[62] J. Ferreira, D. Gaspar, B. Monteiro, A. B. Cruz, F. Porto, and E. Ogasawara, \u201cUma Proposta de Implementa\u00e7\u00e3o de \u00c1lgebra de Workflows em Apache Spark no Apoio a Processos de An\u00e1lise de Dados,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Jul. 2017, pp. 45\u201352. doi: 10.5753\/bresci.2017.9921.<br \/>\n[63] A. Khatibi, F. Porto, J. G. Rittmeyer, E. Ogasawara, P. Valduriez, and D. Shasha, \u201cPre-processing and indexing techniques for constellation queries in big data,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10440 LNCS. pp. 164\u2013172, 2017. doi: 10.1007\/978-3-319-64283-3_12.<br \/>\n[64] F. Paschoal, N. F. F. Ebecken, G. V. S. Ribeiro, L. M. De Aragao Daquer, R. C. Mauro, and E. S. Ogasawara, \u201cFitRank &#8211; Social app to combat physical inactivity study of the use of fitness social apps on Facebook\u2019s users profiles; [FitRank &#8211; Aplicativo Social de Combate ao Sedentarismo Estudo do uso de Aplicativos Sociais de Fitness em perfis de usu\u00e1rios do Facebook],\u201d Iberian Conference on Information Systems and Technologies, CISTI. 2017. doi: 10.23919\/CISTI.2017.7975688.<br \/>\n[65] A. B. Cruz, J. Ferreira, B. Monteiro, R. Coutinho, F. Porto, and E. Ogasawara, \u201cDetec\u00e7\u00e3o de anomalias no transporte rodovi\u00e1rio urbano,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 2017, pp. 240\u2013245.<br \/>\n[66] R. Salles, P. Mattos, E. Bezerra, L. Lima, and E. Ogasawara, \u201cAvalia\u00e7\u00e3o de Agrega\u00e7\u00e3o Temporal na Previs\u00e3o da Temperatura de Superf\u00edcie do Mar do Oceano Atl\u00e2ntico,\u201d in Anais do Concurso de Trabalhos de Inicia\u00e7\u00e3o Cient\u00edfica da SBC (CTIC-SBC), SBC, Jul. 2017.<br \/>\n[67] R. Salles, L. Assis, G. Guedes, E. Bezerra, F. Porto, and E. Ogasawara, \u201cA framework for benchmarking machine learning methods using linear models for univariate time series prediction,\u201d Proceedings of the International Joint Conference on Neural Networks, vol. 2017-May. pp. 2338\u20132345, 2017. doi: 10.1109\/IJCNN.2017.7966139.<br \/>\n[68] R. G. Rodrigues, G. P. Guedes, and E. Ogasawara, \u201cTowards a model for personality-based agents for emotional responses,\u201d WebMedia 2016 &#8211; Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web. pp. 359\u2013362, 2016. doi: 10.1145\/2976796.2988186.<br \/>\n[69] R. Campisano, F. Porto, E. Pacitti, F. Masseglia, and E. Ogasawara, \u201cSpatial Sequential Pattern Mining for Seismic Data,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), Salvador, BA, Oct. 2016.<br \/>\n[70] F. Paschoal, N. F. F. Ebecken, G. V. S. Ribeiro, L. M. De Aragao Daquer, R. C. Mauro, and E. S. Ogasawara, \u201cHealthy behavior with social apps: Proposal for evolution study of the use of fitness social apps on Facebook; [Comportamento Saud\u00e1vel com Aplicativos Sociais: Proposta de estudo de evolu\u00e7\u00e3o do uso de aplicativos sociais de fitness no Facebook],\u201d Iberian Conference on Information Systems and Technologies, CISTI, vol. 2016-July. 2016. doi: 10.1109\/CISTI.2016.7521484.<br \/>\n[71] E. Machado, M. Serqueira, E. Ogasawara, R. Ogando, M. A. G. Maia, L. N. Da Costa, R. Campisano, G. Paiva Guedes, and E. Bezerra, \u201cExploring machine learning methods for the Star\/Galaxy Separation Problem,\u201d Proceedings of the International Joint Conference on Neural Networks, vol. 2016-October. pp. 123\u2013130, 2016. doi: 10.1109\/IJCNN.2016.7727189.<br \/>\n[72] P. Mattos, A. M. Iorgulescu, R. Salles, E. Bezerra, E. Ogasawara, and L. Lima, \u201cUso de Redes Neurais para Previs\u00e3o da Temperatura da Superf\u00edcie do Mar do Oceano Atl\u00e2ntico Tropical,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Aug. 2015, pp. 131\u2013140. doi: 10.5753\/bresci.2015.7214.<br \/>\n[73] E. Machado, E. Bezerra, R. Ogando, M. Maia, L. da Costa, A. F. Neto, and E. Ogasawara, \u201cUm Processo Explorat\u00f3rio para Classifica\u00e7\u00e3o de Estrelas e Gal\u00e1xias,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Aug. 2015, pp. 81\u201390. doi: 10.5753\/bresci.2015.7209.<br \/>\n[74] W. Gomes, P. Castro, E. Cardoso, M. Malheiro, R. Castaneda, G. P. Guedes, R. Mauro, and E. Ogasawara, \u201cProvendo um Servi\u00e7o Web para Intera\u00e7\u00e3o e Coleta de Dados de Aplicativos Educacionais,\u201d in Anais do Simp\u00f3sio Brasileiro de Inform\u00e1tica na Educa\u00e7\u00e3o, Oct. 2015, p. 957. doi: 10.5753\/cbie.sbie.2015.957.<br \/>\n[75] G. P. Guedes, E. Bezerra, E. Ogasawara, and G. Xex\u00e9o, \u201cExploring multiple clusterings in attributed graphs,\u201d Proceedings of the ACM Symposium on Applied Computing, vol. 13-17-April-2015. pp. 915\u2013918, 2015. doi: 10.1145\/2695664.2696008.<br \/>\n[76] E. Honorato, C. O. S. Mendes, J. R. Quadros, R. Castaneda, J. Soares, R. Mauro, S. Duarte, and E. Ogasawara, \u201cExplorando uma Aplica\u00e7\u00e3o m-learning para Ensino de Vetores na F\u00edsica do Ensino M\u00e9dio,\u201d in Anais do Simp\u00f3sio Brasileiro de Inform\u00e1tica na Educa\u00e7\u00e3o, Oct. 2015, p. 1. doi: 10.5753\/cbie.sbie.2015.1.<br \/>\n[77] R. Salles, E. Bezerra, J. Soares, and E. Ogasawara, \u201cEvaluating Linear Models as a Baseline for Time Series Imputation,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), Petr\u00f3polis, RJ, Oct. 2015.<br \/>\n[78] A. B. Cruz, S. Serique, L. Preuss, A. Ogasawara, J. Quadros, E. Bezerra, U. Souza, and E. Ogasawara, \u201cAm\u00ea: An environment to learn and analyze adversarial search algorithms using stochastic card games,\u201d Proceedings of the ACM Symposium on Applied Computing, vol. 13-17-April-2015. pp. 208\u2013213, 2015. doi: 10.1145\/2695664.2695734.<br \/>\n[79] V. Louren\u00e7o, U. Souza, and E. Ogasawara, \u201cUtiliza\u00e7\u00e3o de Algoritmos Gen\u00e9ticos para a Elabora\u00e7\u00e3o do Quadro de Hor\u00e1rios do Ensino M\u00e9dio-T\u00e9cnico Integrado do CEFET\/RJ,\u201d in Anais do Encontro Nacional de Computa\u00e7\u00e3o dos Institutos Federais (ENCompIF), SBC, Jul. 2014, pp. 5\u20138.<br \/>\n[80] F. S. J\u00fanior, K. Belloze, F. P. Jr, E. Bezerra, J. R. Quadros, and E. Ogasawara, \u201cUma Abordagem Simplificada para Experimenta\u00e7\u00e3o de Artefatos em Trabalhos de Conclus\u00e3o de Curso,\u201d in Anais do Workshop sobre Educa\u00e7\u00e3o em Computa\u00e7\u00e3o (WEI), SBC, Jul. 2014, pp. 299\u2013308.<br \/>\n[81] J. T. Pintas, D. De Oliveira, K. A. C. S. Oca\u00f1a, E. Ogasawara, and M. Mattoso, \u201cSciLightning: A cloud provenance-based event notification for parallel workflows,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8377 LNCS. pp. 352\u2013365, 2014. doi: 10.1007\/978-3-319-06859-6_31.<br \/>\n[82] A. Silva, F. Rosa, I. Rocha, F. P. P. Junior, E. Bezerra, G. Guedes, and E. Ogasawara, \u201cRFIDBook: Uma Abordagem para Programas de Bonifica\u00e7\u00e3o Baseada em Redes Sociais,\u201d in Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM), SBC, Aug. 2014, pp. 81\u201392.<br \/>\n[83] L. Paschoal, T. Bento, T. Velasco, C. O. Schocair, R. Castaneda, T. Oliveira, and E. Ogasawara, \u201cJOE: Jogo Ortogr\u00e1fico Educacional,\u201d in Anais do Simp\u00f3sio Brasileiro de Inform\u00e1tica na Educa\u00e7\u00e3o, 2014, p. 652. doi: 10.5753\/cbie.sbie.2014.652.<br \/>\n[84] G. Alves, P. Warley, J. Quadros, L. Lignani, and E. Ogasawara, \u201cControlHarvest: Ensino de Ecologia por Meio de Gamifica\u00e7\u00e3o do Controle Biol\u00f3gico,\u201d in Anais do Simp\u00f3sio Brasileiro de Inform\u00e1tica na Educa\u00e7\u00e3o, 2014, p. 342. doi: 10.5753\/cbie.sbie.2014.342.<br \/>\n[85] R. Machado, M. Santos, H. Soares, E. Ogasawara, F. David, R. Soares, and B. Guimar\u00e3es, \u201cArquitetura de um Simulador em Larga em Escala de Ataques Distribu\u00eddos de Nega\u00e7\u00e3o de Servi\u00e7o,\u201d in Anais do Semin\u00e1rio Integrado de Software e Hardware (SEMISH), SBC, Jul. 2014, pp. 72\u201383.<br \/>\n[86] M. Mattoso, K. Oc\u00e3a, F. Horta, J. Dias, E. Ogasawara, V. Silva, D. De Oliveira, F. Costa, and I. Ara\u00fajo, \u201cUser-steering of HPC workflows: State-of-the-art and future directions,\u201d Proceedings of the 2nd ACM SIGMOD Workshop on Scalable Workflow Execution Engines and Technologies, SWEET 2013. 2013. doi: 10.1145\/2499896.2499900.<br \/>\n[87] V. Silva, J. Dias, D. de Oliveira, E. Ogasawara, and M. Mattoso, \u201cUma Arquitetura P2P de Distribui\u00e7\u00e3o de Atividades para Execu\u00e7\u00e3o Paralela de Workflows Cient\u00edficos,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Jul. 2013, pp. 1795\u20131802.<br \/>\n[88] I. D. Santos, J. Dias, D. D. Oliveira, E. Ogasawara, K. Oca\u00f1a, and M. Mattoso, \u201cRuntime dynamic structural changes of scientific workflows in clouds,\u201d Proceedings &#8211; 2013 IEEE\/ACM 6th International Conference on Utility and Cloud Computing, UCC 2013. pp. 417\u2013422, 2013. doi: 10.1109\/UCC.2013.83.<br \/>\n[89] F. Horta, V. Silva, F. Costa, D. De Oliveira, K. Oca\u00f1a, E. Ogasawara, J. Dias, and M. Mattoso, \u201cProvenance traces from Chiron parallel workflow engine,\u201d ACM International Conference Proceeding Series. pp. 337\u2013338, 2013. doi: 10.1145\/2457317.2457379.<br \/>\n[90] I. de A. dos Santos, J. Dias, D. de Oliveira, E. Ogasawara, and M. Mattoso, \u201cDynAdapt: Altera\u00e7\u00f5es na Defini\u00e7\u00e3o de Atividades de Workflows Cient\u00edficos em Tempo de Execu\u00e7\u00e3o,\u201d in Anais do Brazilian e-Science Workshop (BreSci), SBC, Jul. 2013, pp. 1831\u20131838.<br \/>\n[91] D. De Oliveira, V. Viana, E. Ogasawara, K. Oca\u00f1a, and M. Mattoso, \u201cDimensioning the virtual cluster for parallel scientific workflows in clouds,\u201d ScienceCloud 2013 &#8211; Proceedings of the 4th ACM Workshop on Scientific Cloud Computing. pp. 5\u201312, 2013. doi: 10.1145\/2465848.2465852.<br \/>\n[92] F. Costa, V. Silva, D. De Oliveira, K. Oca\u00f1a, E. Ogasawara, J. Dias, and M. Mattoso, \u201cCapturing and querying workflow runtime provenance with PROV: A practical approach,\u201d ACM International Conference Proceeding Series. pp. 282\u2013289, 2013. doi: 10.1145\/2457317.2457365.<br \/>\n[93] J. Dias, E. Ogasawara, D. De Oliveira, F. Porto, P. Valduriez, and M. Mattoso, \u201cAlgebraic dataflows for big data analysis,\u201d Proceedings &#8211; 2013 IEEE International Conference on Big Data, Big Data 2013. pp. 150\u2013155, 2013. doi: 10.1109\/BigData.2013.6691567.<br \/>\n[94] J. C. de A. Gon\u00e7alves, D. de Oliveira, K. A. Ocana, E. Ogasawara, J. Dias, and M. Mattoso, \u201cUsing Provenance Analyzers to Improve the Performance of Scientific Workflows in Cloud Environments,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 2012.<br \/>\n[95] J. C. D. A. R. Gon\u00e7alves, D. De Oliveira, K. A. C. S. Oca\u00f1a, E. Ogasawara, and M. Mattoso, \u201cUsing domain-specific data to enhance scientific workflow steering queries,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7525 LNCS. pp. 152\u2013167, 2012. doi: 10.1007\/978-3-642-34222-6_12.<br \/>\n[96] F. Costa, D. D. Oliveira, K. Ocana, E. Ogasawara, J. Dias, and M. Mattoso, \u201cHandling failures in parallel scientific workflows using clouds,\u201d Proceedings &#8211; 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012. pp. 129\u2013139, 2012. doi: 10.1109\/SC.Companion.2012.28.<br \/>\n[97] K. A. C. S. Oca\u00f1a, D. De Oliveira, F. Horta, J. Dias, E. Ogasawara, and M. Mattoso, \u201cExploring molecular evolution reconstruction using a parallel cloud based scientific workflow,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7409 LNBI. pp. 179\u2013191, 2012. doi: 10.1007\/978-3-642-31927-3_16.<br \/>\n[98] F. Chirigati, V. Silva, E. Ogasawara, D. De Oliveira, J. Dias, F. Porto, P. Valduriez, and M. Mattoso, \u201cEvaluating parameter sweep workflows in high performance computing,\u201d ACM International Conference Proceeding Series. 2012. doi: 10.1145\/2443416.2443418.<br \/>\n[99] F. Costa, D. De Oliveira, K. A. C. S. Oca\u00f1a, E. Ogasawara, and M. Mattoso, \u201cEnabling re-executions of parallel scientific workflows using runtime provenance data,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7525 LNCS. pp. 229\u2013232, 2012. doi: 10.1007\/978-3-642-34222-6_22.<br \/>\n[100] K. A. C. S. Oca\u00f1a, D. De Oliveira, J. Dias, E. Ogasawara, and M. Mattoso, \u201cDiscovering drug targets for neglected diseases using a pharmacophylogenomic cloud workflow,\u201d 2012 IEEE 8th International Conference on E-Science, e-Science 2012. 2012. doi: 10.1109\/eScience.2012.6404431.<br \/>\n[101] F. Costa, D. De Oliveira, E. Ogasawara, A. A. B. Lima, and M. Mattoso, \u201cAthena: Text mining based discovery of scientific workflows in disperse repositories,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6799 LNCS. pp. 104\u2013121, 2012. doi: 10.1007\/978-3-642-27392-6_8.<br \/>\n[102] F. Horta, J. Dias, K. A. C. S. Oca\u00f1a, D. de Oliveira, E. Ogasawara, and M. Mattoso, \u201cAbstract: Using Provenance to Visualize Data from Large-Scale Experiments,\u201d in 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, Nov. 2012, pp. 1418\u20131419. doi: 10.1109\/SC.Companion.2012.228.<br \/>\n[103] V. Silva, F. Chirigati, E. Ogasawara, J. Dias, D. Oliveira, F. Porto, P. Valduriez, and M. Mattoso, \u201cUma avalia\u00e7\u00e3o da Distribui\u00e7\u00e3o de Atividades Est\u00e1tica e Din\u00e2mica em Ambientes Paralelos usando o Hydra,\u201d in Anais do Brazilian e-Science Workshop (BreSci), 2011, pp. 1\u20138.<br \/>\n[104] J. Dias, E. Ogasawara, D. De Oliveira, F. Porto, A. L. G. A. Coutinho, and M. Mattoso, \u201cSupporting dynamic parameter sweep in adaptive and user-steered workflows,\u201d WORKS\u201911 &#8211; Proceedings of the 6th Workshop on Workflows in Support of Large-Scale Science, Co-located with SC\u201911. pp. 31\u201336, 2011. doi: 10.1145\/2110497.2110502.<br \/>\n[105] K. A. C. S. Oca\u00f1a, D. De Oliveira, E. Ogasawara, A. M. R. D\u00e1vila, A. A. B. Lima, and M. Mattoso, \u201cSciPhy: A cloud-based workflow for phylogenetic analysis of drug targets in protozoan genomes,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6832 LNBI. pp. 66\u201370, 2011. doi: 10.1007\/978-3-642-22825-4_9.<br \/>\n[106] V. Viana, D. de Oliveira, E. Ogasawara, and M. Mattoso, \u201cSciCumulus-ECM: Um Servi\u00e7o de Custos para a Execu\u00e7\u00e3o de Workflows Cient\u00edficos em Nuvens Computacionais,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 2011.<br \/>\n[107] J. Dias, E. Ogasawara, D. De Oliveira, and M. Mattoso, \u201cPoster: Scientific data parallelism using P2P techniques,\u201d SC\u201911 &#8211; Proceedings of the 2011 High Performance Computing Networking, Storage and Analysis Companion, Co-located with SC\u201911. pp. 27\u201328, 2011. doi: 10.1145\/2148600.2148615.<br \/>\n[108] K. A. C. S. Oca\u00f1a, D. De Oliveira, J. Dias, E. Ogasawara, and M. Mattoso, \u201cOptimizing phylogenetic analysis using SciHmm cloud-based scientific workflow,\u201d Proceedings &#8211; 2011 7th IEEE International Conference on eScience, eScience 2011. pp. 62\u201369, 2011. doi: 10.1109\/eScience.2011.17.<br \/>\n[109] D. de Oliveira, E. Ogasawara, F. Baiao, and M. Mattoso, \u201cAdding Ontologies to Scientific Workflow Composition,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 2011.<br \/>\n[110] E. Bezerra, B. Firmino, R. Castaneda, J. Soares, E. Ogasawara, and R. Goldschmidt, \u201cA subjectivity detection method for opinion mining based on lexical resources,\u201d Proceedings of the IADIS International Conference WWW\/Internet 2011, ICWI 2011. pp. 317\u2013324, 2011.<br \/>\n[111] D. De Oliveira, K. Oca\u00f1a, E. Ogasawara, J. Dias, F. Bai\u00e3o, and M. Mattoso, \u201cA performance evaluation of X-ray crystallography scientific workflow using scicumulus,\u201d Proceedings &#8211; 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011. pp. 708\u2013715, 2011. doi: 10.1109\/CLOUD.2011.99.<br \/>\n[112] E. Ogasawara, J. Dias, D. Oliveira, C. Rodrigues, C. Pivotto, R. Antas, V. Braganholo, P. Valduriez, and M. Mattoso, \u201cA P2P approach to many tasks computing for scientific workflows,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6449 LNCS. pp. 327\u2013339, 2011. doi: 10.1007\/978-3-642-19328-6_31.<br \/>\n[113] V. Silva, F. Chirigati, K. Maia, E. Ogasawara, D. Oliveira, V. Braganholo, L. Murta, and M. Mattoso, \u201cSimiFlow: Uma Arquitetura para Agrupamento de Workflows por Similaridade,\u201d in Anais do Brazilian e-Science Workshop (BreSci), 2010, pp. 1\u20138.<br \/>\n[114] J. Dias, C. Rodrigues, E. Ogasawara, D. D. Oliveira, V. Braganholo, E. Pacitti, and M. Mattoso, \u201cSciMulator: Um Ambiente de Simula\u00e7\u00e3o de Workflows Cient\u00edficos em Redes P2P,\u201d presented at the VI Workshop de Redes Din\u00e2micas e Sistemas Peer-to-Peer 2010, May 2010, p. 12.<br \/>\n[115] D. De Oliveira, E. Ogasawara, F. Bai\u00e3o, and M. Mattoso, \u201cSciCumulus: A lightweigh cloud middleware to explore many task computing paradigm in scientific workflows,\u201d Proceedings &#8211; 2010 IEEE 3rd International Conference on Cloud Computing, CLOUD 2010. pp. 378\u2013385, 2010. doi: 10.1109\/CLOUD.2010.64.<br \/>\n[116] A. Marinho, L. Murta, C. Werner, V. Braganholo, E. Ogasawara, S. M. S. Da Cruz, and M. Mattoso, \u201cIntegrating provenance data from distributed workflow systems with ProvManager,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6378 LNCS. pp. 286\u2013288, 2010. doi: 10.1007\/978-3-642-17819-1_35.<br \/>\n[117] J. Dias, E. Ogasawara, D. De Oliveira, E. Pacitti, and M. Mattoso, \u201cImproving many-task computing in scientific workflows using P2P techniques,\u201d 2010 3rd Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS10. 2010. doi: 10.1109\/mtags.2010.5699430.<br \/>\n[118] D. De Oliveira, E. Ogasawara, F. Seabra, V. Silva, L. Murta, and M. Mattoso, \u201cGExpLine: A tool for supporting experiment composition,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6378 LNCS. pp. 251\u2013259, 2010. doi: 10.1007\/978-3-642-17819-1_28.<br \/>\n[119] E. Silva, E. Ogasawara, D. Oliveira, M. Benevides, and M. Mattoso, \u201cEspecifica\u00e7\u00e3o Formal e Verifica\u00e7\u00e3o de Workflows Cient\u00edficos,\u201d in Anais do Brazilian e-Science Workshop (BreSci), 2010.<br \/>\n[120] F. Coutinho, E. Ogasawara, D. De Oliveira, V. Braganholo, A. A. B. Lima, A. M. R. D\u00e1vila, and M. Mattoso, \u201cData parallelism in bioinformatics workflows using Hydra,\u201d HPDC 2010 &#8211; Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing. pp. 507\u2013515, 2010. doi: 10.1145\/1851476.1851550.<br \/>\n[121] E. Ogasawara, L. C. Martinez, D. De Oliveira, G. Zimbr\u00e3o, G. L. Pappa, and M. Mattoso, \u201cAdaptive Normalization: A novel data normalization approach for non-stationary time series,\u201d Proceedings of the International Joint Conference on Neural Networks. 2010. doi: 10.1109\/IJCNN.2010.5596746.<br \/>\n[122] B. Costa, E. Ogasawara, L. Murta, and M. Mattoso, \u201cUma Estrat\u00e9gia de Versionamento de Workflows Cient\u00edficos em Granularidade Fina,\u201d in Anais do Brazilian e-Science Workshop (BreSci), 2009, pp. 49\u201356.<br \/>\n[123] D. de Oliveira, E. Ogasawara, F. Chirigati, V. Sousa, L. Murta, C. Werner, and M. Mattoso, \u201cUma Abordagem Sem\u00e2ntica para Linhas de Experimentos Cient\u00edficos Usando Ontologias,\u201d in Anais do Brazilian e-Science Workshop (BreSci), 2009.<br \/>\n[124] E. Ogasawara, L. Murta, G. Zimbr\u00e3o, and M. Mattoso, \u201cNeural networks cartridges for data mining on time series,\u201d Proceedings of the International Joint Conference on Neural Networks. pp. 2302\u20132309, 2009. doi: 10.1109\/IJCNN.2009.5178615.<br \/>\n[125] E. Ogasawara, D. De Oliveira, F. Chirigati, C. E. Barbosa, R. Elias, V. Braganholo, A. Coutinho, and M. Mattoso, \u201cExploring many task computing in scientific workflows,\u201d Proceedings of the 2nd ACM Workshop on Many-Task Computing on Grids and Supercomputers 2009, MTAGS \u201909. 2009. doi: 10.1145\/1646468.1646470.<br \/>\n[126] E. Ogasawara, C. Paulino, L. Murta, C. Werner, and M. Mattoso, \u201cExperiment line: Software reuse in scientific workflows,\u201d Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5566 LNCS. pp. 264\u2013272, 2009. doi: 10.1007\/978-3-642-02279-1_20.<br \/>\n[127] M. Mattoso, C. Werner, G. Travassos, V. Braganholo, L. Murta, E. Ogasawara, F. Oliveira, and W. Martinho, \u201cDesafios no apoio \u00e0 composi\u00e7\u00e3o de experimentos cient\u00edficos em larga escala,\u201d in Semin\u00e1rio Integrado de Software e Hardware, 2009, p. 36.<br \/>\n[128] E. Ogasawara, P. Rangel, C. Werner, M. Mattoso, and L. Murta, \u201cComparison and versioning of scientific workflows,\u201d Proceedings of the 2009 ICSE Workshop on Comparison and Versioning of Software Models, CVSM 2009. pp. 25\u201330, 2009. doi: 10.1109\/CVSM.2009.5071718.<br \/>\n[129] E. Ogasawara, L. Murta, C. Werner, and M. Mattoso, \u201cLinhas de Experimento: Reutiliza\u00e7\u00e3o e Ger\u00eancia de Configura\u00e7\u00e3o em Workflows Cient\u00edficos,\u201d in Anais do Brazilian e-Science Workshop (BreSci), 2008, pp. 31\u201340.<br \/>\n[130] E. Ogasawara and M. Mattoso, \u201cUma Avalia\u00e7\u00e3o Experimental sobre T\u00e9cnicas de Indexa\u00e7\u00e3o em Bancos de Dados Orientados a Objetos,\u201d in Anais do Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), 1999, pp. 1\u201313.<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Journals [1] R. Salles, B. Lange, R. Akbarinia, F. Masseglia, E. Ogasawara, and E. Pacitti, \u201cScalable and accurate online multivariate anomaly detection,\u201d Information Systems, vol. 131, p. 102524, Jun. 2025, doi: 10.1016\/j.is.2025.102524. [2] R. Salles, J. Lima, M. Reis, R. Coutinho, E. Pacitti, F. Masseglia, R. Akbarinia, C. Chen, J. Garibaldi, F. Porto, and E. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1768","page","type-page","status-publish","hentry","entry"],"_links":{"self":[{"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/pages\/1768","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/comments?post=1768"}],"version-history":[{"count":3,"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/pages\/1768\/revisions"}],"predecessor-version":[{"id":1775,"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/pages\/1768\/revisions\/1775"}],"wp:attachment":[{"href":"https:\/\/eic.cefet-rj.br\/~dal\/wp-json\/wp\/v2\/media?parent=1768"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}