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| Registros recuperados : 26 | |
| 8. |  | CHINO, D. Y. T.; GONCALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Discovering frequent patterns on agrometeorological data with TrieMotif. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16., 2014, Lisbon. Enterprise information systems: ICEIS 2014: revised selected papers. Switzerland: Springer, 2015. p. 91-107. (Lecture notes in business information processing, 227). Editores: José Cordeiro, Slimane Hammoudi, Leszek Maciaszek, Olivier Camp, Joaquim Filipe.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 11. | | CHINO, D. Y. T.; GONÇALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. TrieMotif: a new and efficient method to mine frequent K-motifs from large time series. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress, 2014. p. 60-69. ICEIS 2014.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 12. | | ROMANI, L. A. S.; GONÇALVES, R. R. do V.; AMARAL, B. F. do; ZULLO JUNIOR, J.; TRAINA JUNIOR, C.; SOUSA, E. P. M. de; TRAINA, A. J. M. Acompanhamento de safras de cana-de-açúcar por meio de técnicas de agrupamento em séries temporais de NDVI. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011. p. 1-8. SBSR 2011.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 13. | | NUNES, S. A.; ROMANI, L. A. S.; AVILA, A. M. H.; TRAINA JÚNIOR, C.; SOUSA, E. P. M. de; TRAINA, A. J. M. Análise baseada em fractais para identificação de mudanças de tendências em múltiplas séries climáticas. In: BRAZILIAN SYMPOSIUM ON DATABASES, 25., 2010, Belo Horizonte. Proceedings... Belo Horizonte: UFMG, 2010. p. 65-72. SBBD 2010.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 14. | | ROMANI, L. A. S.; TRAINA, A. J. M.; RIBEIRO, M. X.; SOUSA, E. P. M. de; ZULLO JUNIOR, J.; TRAINA JUNIOR, C. Aplicação de técnicas de mineração em dados climáticos e de satélite para auxiliar no acompanhamento das safras de cana-de-acúcar. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS, 23.; SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SOFTWARE, 22.; WORKSHOP EM ALGORITMOS E APLICAÇÕES DE MINERAÇÃO DE DADOS, 4., 2008, Campinas. Anais... Campinas: UNICAMP, Instituto de Computação, 2008. p. 87-92.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 15. | | COLTRI, P. P.; CORDEIRO, R. L. F.; SOUZA, T. T. de; ROMANI, L. A. S.; ZULLO JÚNIOR, J.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Classificação de áreas de café em Minas Gerais por meio do novo algoritmo QMAS em imagem espectral Geoeye-1. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011. p. 0539-0546. SBSR 2011.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 16. | | ROMANI, L. A. S.; CHINO, D. Y. T.; AVALHAIS, L. P. S.; OLIVEIRA, W. D.; GONÇALVES, R. R. V.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Involving users in the gestural language definition process for the NInA framework. In: BRAZILIAN SYMPOSIUM ON HUMAN FACTORS IN COMPUTING SYSTEMS, 12., 2013, Manaus. Proceedings... Porto Alegre: SBC, 2013. p. 280-283. IHC 2013.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 17. | | ROMANI, L. A. S.; SOUSA, E. P. M. de; RIBEIRO, M. X.; ÁVILA, A. M. H. de; ZULLO JÚNIOR, J.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Mining climate and remote sensing time series to improve monitoring of sugar cane fields. In: PRADO, H. A. do; LUIZ, A. J. B.; CHAIB FILHO, H. Computational Methods for Agricultural Research: Advances and Applications. Hershey: Information Science Reference, 2011. chap. 4, p. 50-72.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 18. | | ROMANI, L. A. S.; AVILA, A. M. H. de; CHINO, D. Y. T.; ZULLO JÚNIOR, J.; CHBEIR, R.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. A new time series mining approach applied to multitemporal remote sensing imagery. IEEE transactions on geoscience and remote sensing, New York, v. 51, n. 1, p. 140-150, Jan. 2013.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 19. | | CHINO, D. Y. T.; ROMANI, L. A. S.; AVALHAIS, L. P. S.; OLIVEIRA, W. D.; GONÇALVES, R. R. V.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. The NInA Framework using gesture to improve interaction and collaboration in geographical information systems. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 15.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 8., 2013, Angers Loire Valley. Proceedings... [S.l.]: Scitepress, 2013. p. 35-43. ICEIS 2013. ENASE 2013.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 20. | | ROMANI, L. A. S.; SOUSA, E. P. M. de; RIBEIRO, M. X.; ZULLO JÚNIOR. J.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Employing fractal dimension to analyze climate and remote sensing data streams. In: SIAM INTERNATIONAL CONFERENCE ON DATA MINING, 9., 2009, Sparks. Proceedings... Society for Industrial and Applied Mathematics, Philadelphia, 2009. Não paginado. SDM 2009.| Biblioteca(s): Embrapa Agricultura Digital. |
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| Registros recuperados : 26 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
25/05/2009 |
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Data da última atualização: |
15/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
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Autoria: |
ROMANI, L. A. S.; SOUSA, E. P. M. de; RIBEIRO, M. X.; ZULLO JÚNIOR. J.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. |
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Afiliação: |
LUCIANA ALVIM SANTOS ROMANI, CNPTIA; ELAINE P. M. DE SOUSA, ICMC/USP; MARCELA X. RIBEIRO, ICMC/USP; JURANDIR ZULLO JÚNIOR, CEPAGRI/UNICAMP; CAETANO TRAINA JÚNIOR, ICMC/USP; AGMA J. M. TRAINA, ICMC/USP. |
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Título: |
Employing fractal dimension to analyze climate and remote sensing data streams. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: SIAM INTERNATIONAL CONFERENCE ON DATA MINING, 9., 2009, Sparks. Proceedings... Society for Industrial and Applied Mathematics, Philadelphia, 2009. |
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Páginas: |
Não paginado. |
|
Idioma: |
Inglês |
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Notas: |
SDM 2009. |
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Conteúdo: |
Recently, huge amounts of climate data and remote sensing images have been stored by several institutions around the world. Improvements in the data gathering, aiming at making it available to the domain specialist the information needed for decision making. Also, data usually change their behavior over time in climate and remote sensing areas, evolving according to agrometeorological aspects. In this work, we propose a framework to monitor evolving climate and remote sensing data by emplooying a fast and low-cost process based on the fractal dimension extracted from the collected data. Significant changes in data trends are captured by the fractal-based monitoring process. The changes are evaluated by employing a statistical test to compare the data in consecutive time periods, revealing which data attributes are responsible for the trend changes and how they influence them. Therefore, the proposed framework monitors and reveals important variations on the climate that should be considered to make the agribusiness of the remote sense regions more productive. In particular, we show that the information and knowledge discovered from this framework can be employed to monitor sugar cane crops, helping agricultural entrepreneurs to make decisions in order to become more productive. |
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Palavras-Chave: |
Dados multimídia; Data streams; Dimensão fractal; Inteligência artificial; Multimedia data; Teoria dos fractais. |
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Thesagro: |
Agricultura; Clima; Sensoriamento remoto. |
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Thesaurus NAL: |
Climate; Fractal dimensions; Remote sensing. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 02363nam a2200337 a 4500
001 1048990
005 2020-01-15
008 2009 bl uuuu u00u1 u #d
100 1 $aROMANI, L. A. S.
245 $aEmploying fractal dimension to analyze climate and remote sensing data streams.$h[electronic resource]
260 $aIn: SIAM INTERNATIONAL CONFERENCE ON DATA MINING, 9., 2009, Sparks. Proceedings... Society for Industrial and Applied Mathematics, Philadelphia$c2009
300 $aNão paginado.
500 $aSDM 2009.
520 $aRecently, huge amounts of climate data and remote sensing images have been stored by several institutions around the world. Improvements in the data gathering, aiming at making it available to the domain specialist the information needed for decision making. Also, data usually change their behavior over time in climate and remote sensing areas, evolving according to agrometeorological aspects. In this work, we propose a framework to monitor evolving climate and remote sensing data by emplooying a fast and low-cost process based on the fractal dimension extracted from the collected data. Significant changes in data trends are captured by the fractal-based monitoring process. The changes are evaluated by employing a statistical test to compare the data in consecutive time periods, revealing which data attributes are responsible for the trend changes and how they influence them. Therefore, the proposed framework monitors and reveals important variations on the climate that should be considered to make the agribusiness of the remote sense regions more productive. In particular, we show that the information and knowledge discovered from this framework can be employed to monitor sugar cane crops, helping agricultural entrepreneurs to make decisions in order to become more productive.
650 $aClimate
650 $aFractal dimensions
650 $aRemote sensing
650 $aAgricultura
650 $aClima
650 $aSensoriamento remoto
653 $aDados multimídia
653 $aData streams
653 $aDimensão fractal
653 $aInteligência artificial
653 $aMultimedia data
653 $aTeoria dos fractais
700 1 $aSOUSA, E. P. M. de
700 1 $aRIBEIRO, M. X.
700 1 $aZULLO JÚNIOR. J.
700 1 $aTRAINA JÚNIOR, C.
700 1 $aTRAINA, A. J. M.
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