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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Milho e Sorgo; Embrapa Pantanal; Embrapa Territorial. |
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Data corrente: |
04/11/2020 |
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Data da última atualização: |
11/11/2020 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
TERNES, S.; MOURA, M. F.; SOUZA, K. X. S. de; VAZ, G. J.; OLIVEIRA, S. R. de M.; HIGA, R. H.; LIMA, H. P. de; TAKEMURA, C. M.; COELHO, E. A.; BARBOSA, F. F. L.; VISOLI, M. C.; MENEZES, G. R. de O.; SILVA, L. O. C. da; SANTOS, S. A.; MASSRUHÁ, S. M. F. S.; ABREU, U. G. P. de; SORIANO, B. M. A.; SALIS, S. M.; OLIVEIRA, M. D. de; TOMAS, W. M. |
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Afiliação: |
SONIA TERNES, CNPTIA; MARIA FERNANDA MOURA, CNPTIA; KLEBER XAVIER SAMPAIO DE SOUZA, CNPTIA; GLAUBER JOSE VAZ, CNPTIA; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; ROBERTO HIROSHI HIGA, CNPTIA; HELANO POVOAS DE LIMA, CNPTIA; CELINA MAKI TAKEMURA, CNPM; ENILDA ALVES COELHO, CNPMS; FRANCISCO FERRAZ LARANJEIRA BARBOSA, CNPMF; MARCOS CEZAR VISOLI, CNPTIA; GILBERTO ROMEIRO DE OLIVEIRA MENEZES, CNPGC; LUIZ OTAVIO CAMPOS DA SILVA, CNPGC; SANDRA APARECIDA SANTOS, CPAP; SILVIA MARIA FONSECA S MASSRUHA, CNPTIA; URBANO GOMES PINTO DE ABREU, CPAP; BALBINA MARIA ARAUJO SORIANO, CPAP; SUZANA MARIA DE SALIS, CPAP; MARCIA DIVINA DE OLIVEIRA, CPAP; WALFRIDO MORAES TOMAS, CPAP. |
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Título: |
Computação científica na agricultura. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
In: MASSRUHÁ, S. M. F. S.; LEITE, M. A. de A.; OLIVEIRA, S. R. de M.; MEIRA, C. A. A.; LUCHIARI JUNIOR, A.; BOLFE, E. L. (Ed.). Agricultura digital: pesquisa, desenvolvimento e inovação nas cadeias produtivas. Brasília, DF: Embrapa, 2020. cap. 5, p. 120-144. |
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ISBN: |
978-65-86056-37-2 |
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Idioma: |
Português |
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Notas: |
Na publicação: Enilda Coelho, Suzana Maria Salis. |
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Conteúdo: |
Introdução. Inteligência artificial. Classificação automática de solos. Sistema especialista baseado no SiBCS. Sistema inteligente de classificação de solos. Mineração de textos em publicações técnico-científicas. Modelagem matemática e estatística. Modelagem da dinâmica de dispersão do "HLB do citros". Avaliação genética de animais. Fazenda Pantaneira Sustentável (FPS). O software FPS. Considerações finais. |
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Palavras-Chave: |
Agricultura digital; Aprendizado de máquina; Computação científica; Digital agriculture; Inteligência Artificial; Machine learning; Mineração de textos; Modelagem matemática; Text mining; Transformação digital na agricultura. |
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Thesagro: |
Agricultura; Análise Estatística. |
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Thesaurus Nal: |
Agriculture; Artificial intelligence; Mathematical models; Statistical analysis. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/217702/1/LV-Agricultura-digital-2020-cap5.pdf
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/1126229/1/LV-Agricultura-digital-2020-cap5.pdf
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Marc: |
LEADER 02293naa a2200565 a 4500
001 2126229
005 2020-11-11
008 2020 bl uuuu u00u1 u #d
020 $a978-65-86056-37-2
100 1 $aTERNES, S.
245 $aComputação científica na agricultura.$h[electronic resource]
260 $c2020
500 $aNa publicação: Enilda Coelho, Suzana Maria Salis.
520 $aIntrodução. Inteligência artificial. Classificação automática de solos. Sistema especialista baseado no SiBCS. Sistema inteligente de classificação de solos. Mineração de textos em publicações técnico-científicas. Modelagem matemática e estatística. Modelagem da dinâmica de dispersão do "HLB do citros". Avaliação genética de animais. Fazenda Pantaneira Sustentável (FPS). O software FPS. Considerações finais.
650 $aAgriculture
650 $aArtificial intelligence
650 $aMathematical models
650 $aStatistical analysis
650 $aAgricultura
650 $aAnálise Estatística
653 $aAgricultura digital
653 $aAprendizado de máquina
653 $aComputação científica
653 $aDigital agriculture
653 $aInteligência Artificial
653 $aMachine learning
653 $aMineração de textos
653 $aModelagem matemática
653 $aText mining
653 $aTransformação digital na agricultura
700 1 $aMOURA, M. F.
700 1 $aSOUZA, K. X. S. de
700 1 $aVAZ, G. J.
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aHIGA, R. H.
700 1 $aLIMA, H. P. de
700 1 $aTAKEMURA, C. M.
700 1 $aCOELHO, E. A.
700 1 $aBARBOSA, F. F. L.
700 1 $aVISOLI, M. C.
700 1 $aMENEZES, G. R. de O.
700 1 $aSILVA, L. O. C. da
700 1 $aSANTOS, S. A.
700 1 $aMASSRUHÁ, S. M. F. S.
700 1 $aABREU, U. G. P. de
700 1 $aSORIANO, B. M. A.
700 1 $aSALIS, S. M.
700 1 $aOLIVEIRA, M. D. de
700 1 $aTOMAS, W. M.
773 $tIn: MASSRUHÁ, S. M. F. S.; LEITE, M. A. de A.; OLIVEIRA, S. R. de M.; MEIRA, C. A. A.; LUCHIARI JUNIOR, A.; BOLFE, E. L. (Ed.). Agricultura digital: pesquisa, desenvolvimento e inovação nas cadeias produtivas. Brasília, DF: Embrapa, 2020. cap. 5, p. 120-144.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
18/09/2012 |
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Data da última atualização: |
22/04/2013 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
C - 0 |
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Autoria: |
ALVARENGA NETO, R. C. D. de; VIEIRA, J. L. G. |
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Afiliação: |
RIVADÁVIA CORREA DRUMMOND de ALVARENGA NETO, FUNDAÇÃO DOM CABRAL; JOB LUCIO GOMES VIEIRA, SGE. |
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Título: |
Building a Knowledge Management Model at Brazil's Embrapa (Brazilian Agricultural Research Corporation): Towards a Knowledge-Based View of Organizations. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
The Electronic Journal of Knowledge Management, v. 9, issue 2, p. 85-97. |
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Idioma: |
Inglês |
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Conteúdo: |
This paper investigates and analyses the process of building a knowledge management (KM) model at Brazil‟s Embrapa (The Brazilian Agricultural Research Corporation). Embrapa is a world class knowledge organization whose mission is to provide feasible solutions for the sustainable development of Brazilian agribusiness through knowledge and technology generation and transfer. The qualitative research strategy used was the study of a single case with incorporated units of analysis and two criteria were observed for the judgment of the quality of the research project: validity of the construct and reliability. Multiple sources of evidence were used and data analysis consisted of three flows of activities: data reduction, data displays and conclusion drawing/verification. The results revealed a robust KM model made of four dynamic axes: (i) strategy (a strategic conception of information and knowledge use), (ii) environment - four different groups of enabling conditions (social-behavioral, information/communication, cognitive/epistemic and business/managerial), sine qua non conditions for successful implementation, (iii) tool box ? sets of IT tools and managerial practices and (iv) results ? in terms of outputs, being both tangible and intangible assets. The conclusions suggest that a collaborative building of a KM model in a diverse and geographically dispersed organization is more likely to succeed than one that is build and implemented from the top-down perspective. Embrapa‟s KM Model is more inclined to be a knowledge-based view of organization than merely a KM model. Limitations of the study and suggestions for future research are also discussed. MenosThis paper investigates and analyses the process of building a knowledge management (KM) model at Brazil‟s Embrapa (The Brazilian Agricultural Research Corporation). Embrapa is a world class knowledge organization whose mission is to provide feasible solutions for the sustainable development of Brazilian agribusiness through knowledge and technology generation and transfer. The qualitative research strategy used was the study of a single case with incorporated units of analysis and two criteria were observed for the judgment of the quality of the research project: validity of the construct and reliability. Multiple sources of evidence were used and data analysis consisted of three flows of activities: data reduction, data displays and conclusion drawing/verification. The results revealed a robust KM model made of four dynamic axes: (i) strategy (a strategic conception of information and knowledge use), (ii) environment - four different groups of enabling conditions (social-behavioral, information/communication, cognitive/epistemic and business/managerial), sine qua non conditions for successful implementation, (iii) tool box ? sets of IT tools and managerial practices and (iv) results ? in terms of outputs, being both tangible and intangible assets. The conclusions suggest that a collaborative building of a KM model in a diverse and geographically dispersed organization is more likely to succeed than one that is build and implemented from the top-down perspective. Embr... Mostrar Tudo |
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Palavras-Chave: |
Embrapa; Knowledge management; Organization. |
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Thesagro: |
Agronegócio. |
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Thesaurus NAL: |
sustainable development. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/66503/1/ejkm-volume9-issue2-article283.pdf
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Marc: |
LEADER 02364naa a2200193 a 4500
001 1933995
005 2013-04-22
008 2012 bl uuuu u00u1 u #d
100 1 $aALVARENGA NETO, R. C. D. de
245 $aBuilding a Knowledge Management Model at Brazil's Embrapa (Brazilian Agricultural Research Corporation)$bTowards a Knowledge-Based View of Organizations.$h[electronic resource]
260 $c2012
520 $aThis paper investigates and analyses the process of building a knowledge management (KM) model at Brazil‟s Embrapa (The Brazilian Agricultural Research Corporation). Embrapa is a world class knowledge organization whose mission is to provide feasible solutions for the sustainable development of Brazilian agribusiness through knowledge and technology generation and transfer. The qualitative research strategy used was the study of a single case with incorporated units of analysis and two criteria were observed for the judgment of the quality of the research project: validity of the construct and reliability. Multiple sources of evidence were used and data analysis consisted of three flows of activities: data reduction, data displays and conclusion drawing/verification. The results revealed a robust KM model made of four dynamic axes: (i) strategy (a strategic conception of information and knowledge use), (ii) environment - four different groups of enabling conditions (social-behavioral, information/communication, cognitive/epistemic and business/managerial), sine qua non conditions for successful implementation, (iii) tool box ? sets of IT tools and managerial practices and (iv) results ? in terms of outputs, being both tangible and intangible assets. The conclusions suggest that a collaborative building of a KM model in a diverse and geographically dispersed organization is more likely to succeed than one that is build and implemented from the top-down perspective. Embrapa‟s KM Model is more inclined to be a knowledge-based view of organization than merely a KM model. Limitations of the study and suggestions for future research are also discussed.
650 $asustainable development
650 $aAgronegócio
653 $aEmbrapa
653 $aKnowledge management
653 $aOrganization
700 1 $aVIEIRA, J. L. G.
773 $tThe Electronic Journal of Knowledge Management$gv. 9, issue 2, p. 85-97.
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Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
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