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Registro Completo |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
24/08/2001 |
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Data da última atualização: |
24/08/2001 |
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Autoria: |
ZARUR, S. B. |
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Título: |
Vila Planalto: um caso de resistencia popular. |
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Ano de publicação: |
1996 |
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Fonte/Imprenta: |
In: PAVIANI, A. (Org.). Brasilia moradia e exclusao. Brasilia: Ed. Universidade de Brasilia, 1996. p. 81-113. |
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Idioma: |
Português |
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Palavras-Chave: |
Brasilia; Preservacao historica; Resistance; Survival; Vila Planalto. |
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Thesagro: |
População; Resistência; Sobrevivência. |
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Thesaurus Nal: |
population. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00621naa a2200217 a 4500
001 1103851
005 2001-08-24
008 1996 bl uuuu u00u1 u #d
100 1 $aZARUR, S. B.
245 $aVila Planalto$bum caso de resistencia popular.
260 $c1996
650 $apopulation
650 $aPopulação
650 $aResistência
650 $aSobrevivência
653 $aBrasilia
653 $aPreservacao historica
653 $aResistance
653 $aSurvival
653 $aVila Planalto
773 $tIn: PAVIANI, A. (Org.). Brasilia moradia e exclusao. Brasilia: Ed. Universidade de Brasilia, 1996. p. 81-113.
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Embrapa Unidades Centrais (AI-SEDE) |
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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. |
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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 |
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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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