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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. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
19/12/2013 |
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Data da última atualização: |
08/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
NUNES, S. A.; ROMANI, L. A. S.; AVILA, A. M. H.; COLTRI, P. P.; TRAINA, A. J. M.; SOUSA, E. P. M. |
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Afiliação: |
SANTIAGO A. NUNES, ICMC/USP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; ANA M. H. AVILA, Cepagri/Unicamp; PRISCILA P. COLTRI, Cepagri/Unicamp; AGMA J. M. TRAINA, ICMC/USP; ELAINE P. M. SOUSA, ICMC/USP. |
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Título: |
Finding spatio-temporal patterns in multidimensional data streams. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Journal of Information and Data Management, v. 4, n. 3, p. 327-340, Oct. 2013. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract. In the last few decades, advances in data acquisition technology have contributed to generation of huge volumes of data in diverse application areas, creating new research challenges in knowledge discovery. The analysis of these data has become an important task in several domains such as sensor networks, web-logs, financial transactions and climate change monitoring. In this article, we propose the Spatio-Temporal Behavior Meter (STB-meter) method to identify spatio-temporal patterns in multidimensional evolving data streams. Our approach combines a multi-resolution hierarchical structure to deal with spatial information with fractal-based analysis to monitor non spatial information of the multidimensional data stream. Experimental evaluation on real climate data shows that our method allows finding relevant spatio-temporal patterns in evolving data at different spatial and temporal resolutions and therefore it can be a useful tool to assist domain specialists in climate change researches. |
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Palavras-Chave: |
Dados espaço temporais; Fractal; Spatio-temporal data. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01666naa a2200217 a 4500
001 1974395
005 2020-01-08
008 2013 bl uuuu u00u1 u #d
100 1 $aNUNES, S. A.
245 $aFinding spatio-temporal patterns in multidimensional data streams.$h[electronic resource]
260 $c2013
520 $aAbstract. In the last few decades, advances in data acquisition technology have contributed to generation of huge volumes of data in diverse application areas, creating new research challenges in knowledge discovery. The analysis of these data has become an important task in several domains such as sensor networks, web-logs, financial transactions and climate change monitoring. In this article, we propose the Spatio-Temporal Behavior Meter (STB-meter) method to identify spatio-temporal patterns in multidimensional evolving data streams. Our approach combines a multi-resolution hierarchical structure to deal with spatial information with fractal-based analysis to monitor non spatial information of the multidimensional data stream. Experimental evaluation on real climate data shows that our method allows finding relevant spatio-temporal patterns in evolving data at different spatial and temporal resolutions and therefore it can be a useful tool to assist domain specialists in climate change researches.
653 $aDados espaço temporais
653 $aFractal
653 $aSpatio-temporal data
700 1 $aROMANI, L. A. S.
700 1 $aAVILA, A. M. H.
700 1 $aCOLTRI, P. P.
700 1 $aTRAINA, A. J. M.
700 1 $aSOUSA, E. P. M.
773 $tJournal of Information and Data Management$gv. 4, n. 3, p. 327-340, Oct. 2013.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Mandioca e Fruticultura. Para informações adicionais entre em contato com cnpmf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
28/12/2011 |
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Data da última atualização: |
01/11/2013 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
SAMPAIO, L. F. S.; MORAIS-LINO, L. S.; SEREJO, J. A. dos S. |
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Afiliação: |
LUCYMEIRE SOUZA MORAIS-LINO, UEFS; JANAY ALMEIDA DOS SANTOS SEREJO, CNPMF. |
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Título: |
Cell suspension from the banana cultivar 'Tropical' (AAAB). |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: PROMUSA SYMPOSIUM, 2011, Salvador. Bananas and plantains: toward sustainable global production and improved uses: abstracts. [S.l.]: [ISHS], 2011. p. 123. |
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Idioma: |
Inglês |
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Conteúdo: |
'Tropical' (AAAB) is a banana hybrid generated at Embrapa, decived from a cross between 'Yangambi No. 2' (AAB) and 'M53' (AA), which is similar to 'Silk' for most of its features, such as development and yield. |
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Palavras-Chave: |
Growth curve; Mussa spp. |
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Thesagro: |
Banana. |
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Thesaurus NAL: |
tissue culture. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 00821nam a2200181 a 4500
001 1911112
005 2013-11-01
008 2011 bl uuuu u00u1 u #d
100 1 $aSAMPAIO, L. F. S.
245 $aCell suspension from the banana cultivar 'Tropical' (AAAB).
260 $aIn: PROMUSA SYMPOSIUM, 2011, Salvador. Bananas and plantains: toward sustainable global production and improved uses: abstracts. [S.l.]: [ISHS], 2011. p. 123.$c2011
520 $a'Tropical' (AAAB) is a banana hybrid generated at Embrapa, decived from a cross between 'Yangambi No. 2' (AAB) and 'M53' (AA), which is similar to 'Silk' for most of its features, such as development and yield.
650 $atissue culture
650 $aBanana
653 $aGrowth curve
653 $aMussa spp
700 1 $aMORAIS-LINO, L. S.
700 1 $aSEREJO, J. A. dos S.
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