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Registro Completo |
Biblioteca(s): |
Embrapa Rondônia. |
Data corrente: |
01/10/2003 |
Data da última atualização: |
01/10/2003 |
Autoria: |
TEIXEIRA, J. B.; MARBACH, P. A. S.; SANTOS, M. de O. |
Título: |
Otimização da metodologia de embriogênese somática visando a propagação clonal de genótipo elite de cacau (Theobroma cacao L.). |
Ano de publicação: |
2003 |
Fonte/Imprenta: |
Brasília: Embrapa Recursos Genéticos e Biotecnologia, 2003. |
Páginas: |
34 p. |
Série: |
(Embrapa Recursos Genéticos e Biotecnologia. Documentos, 79). |
Idioma: |
Português |
Palavras-Chave: |
Propagação Clonal. |
Thesagro: |
Cacau; Embriogénese. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00638nam a2200181 a 4500 001 1704446 005 2003-10-01 008 2003 bl uuuu u0uu1 u #d 100 1 $aTEIXEIRA, J. B. 245 $aOtimização da metodologia de embriogênese somática visando a propagação clonal de genótipo elite de cacau (Theobroma cacao L.). 260 $aBrasília: Embrapa Recursos Genéticos e Biotecnologia$c2003 300 $a34 p. 490 $a(Embrapa Recursos Genéticos e Biotecnologia. Documentos, 79). 650 $aCacau 650 $aEmbriogénese 653 $aPropagação Clonal 700 1 $aMARBACH, P. A. S. 700 1 $aSANTOS, M. de O.
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Embrapa Rondônia (CPAF-RO) |
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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
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
04/12/2014 |
Data da última atualização: |
08/01/2020 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
CHINO, D. Y. T.; GONÇALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. |
Afiliação: |
DANIEL Y. T. CHINO, ICMC/USP; RENATA R. V. GONÇALVES, Cepagri/Unicamp; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; CAETANO TRAINA JÚNIOR, ICMC/USP; AGMA J. M. TRAINA, ICMC/USP. |
Título: |
TrieMotif: a new and efficient method to mine frequent K-motifs from large time series. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
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. |
Páginas: |
p. 60-69. |
ISBN: |
978-989-758-027-7 |
Idioma: |
Inglês |
Notas: |
ICEIS 2014. |
Conteúdo: |
Abstract: Finding previously unknown patterns that frequently occur on time series is a core task of mining time series. These patterns are known as time series motifs and are essential to associate events and meaningful occurrences within the time series. In this work we propose a method based on a trie data structure, that allows a fast and accurate time series motif discovery. From the experiments performed on synthetic and real data we can see that our TrieMotif approach is able to efficiently find motifs even when the size of the time series goes longer, being in average 3 times faster and requiring 10 times less memory than the state of the art approach. As a case study on real data, we also evaluated our method using time series extracted from remote sensing images regarding sugarcane crops. Our proposed method was able to find relevant patterns, as sugarcane cycles and other land covers inside the same area. |
Palavras-Chave: |
AVHRR-NOAA images; Imagens AVHRR-NOAA; Imagens de satélite; Séries temporais. |
Thesagro: |
Sensoriamento Remoto. |
Thesaurus NAL: |
Remote sensing; Time series analysis. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 01925nam a2200277 a 4500 001 2001713 005 2020-01-08 008 2014 bl uuuu u00u1 u #d 020 $a978-989-758-027-7 100 1 $aCHINO, D. Y. T. 245 $aTrieMotif$ba new and efficient method to mine frequent K-motifs from large time series.$h[electronic resource] 260 $aIn: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress$c2014 300 $ap. 60-69. 500 $aICEIS 2014. 520 $aAbstract: Finding previously unknown patterns that frequently occur on time series is a core task of mining time series. These patterns are known as time series motifs and are essential to associate events and meaningful occurrences within the time series. In this work we propose a method based on a trie data structure, that allows a fast and accurate time series motif discovery. From the experiments performed on synthetic and real data we can see that our TrieMotif approach is able to efficiently find motifs even when the size of the time series goes longer, being in average 3 times faster and requiring 10 times less memory than the state of the art approach. As a case study on real data, we also evaluated our method using time series extracted from remote sensing images regarding sugarcane crops. Our proposed method was able to find relevant patterns, as sugarcane cycles and other land covers inside the same area. 650 $aRemote sensing 650 $aTime series analysis 650 $aSensoriamento Remoto 653 $aAVHRR-NOAA images 653 $aImagens AVHRR-NOAA 653 $aImagens de satélite 653 $aSéries temporais 700 1 $aGONÇALVES, R. R. V. 700 1 $aROMANI, L. A. S. 700 1 $aTRAINA JÚNIOR, C. 700 1 $aTRAINA, A. J. M.
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