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 | Acesso ao texto completo restrito à biblioteca da Embrapa Unidades Centrais. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
11/06/2010 |
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Data da última atualização: |
23/09/2019 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
PRADO, H. A. do; FERNEDA, E.; ANQUETIL, N.; TEIXEIRA, E. D'A. |
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Afiliação: |
HERCULES ANTONIO DO PRADO, SGE; EDILSON FERNEDA, Universidade Católica de Brasília; NICOLAS ANQUETIL, Universidade Católica de Brasília; ELIZABETH D'ARROCHELLA, Universidade Católica de Brasília. |
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Título: |
Counselor, a data mining based time estimation for software maintenance. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: In: VELÁSQUEZ, J. D.; RÍOS, S. A.; HOWLETT, R. J.; JAIN, L., C. (Ed.). Knowledge-Based and Intelligent Information and Engineering Systems 13th International Conference, KES 2009, Santiago, Chile, September 28-30, 2009, Proceedings, Part II. |
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Volume: |
5712 |
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Páginas: |
p. 364-371 |
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Série: |
(Lecture Notes in Computer Science - LNCS, 5712). |
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DOI: |
10.1007/978-3-642-04592-9_46 |
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Idioma: |
Inglês |
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Conteúdo: |
Measuring and estimating are fundamental activities for the success of any project. In the software maintenance realm the lack of maturity, or even a low level of interest in adopting effective maintenance techniques and related metrics, have been pointed out as an important cause for the high costs involved. In this paper data mining techniques are applied to provide a sound estimation for the time required to accomplish a maintenance task. Based on real world data regarding maintenance requests, some regression models are built to predict the time required for each maintenance. Data on the team skill and the maintenance characteristics are mapped into values that predict better time estimations in comparison to the one predicted by the human expert. A particular finding from this research is that the time prediction provided by a human expert works as an inductive bias that improves the overall prediction accuracy. |
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Palavras-Chave: |
Data mining; Informal reasoning; Software maintenance. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01828nam a2200217 a 4500
001 1854902
005 2019-09-23
008 2009 bl uuuu u00u1 u #d
024 7 $a10.1007/978-3-642-04592-9_46$2DOI
100 1 $aPRADO, H. A. do
245 $aCounselor, a data mining based time estimation for software maintenance.$h[electronic resource]
260 $aIn: In: VELÁSQUEZ, J. D.; RÍOS, S. A.; HOWLETT, R. J.; JAIN, L., C. (Ed.). Knowledge-Based and Intelligent Information and Engineering Systems 13th International Conference, KES 2009, Santiago, Chile, September 28-30, 2009, Proceedings, Part II.$c2009
300 $ap. 364-371 5712
490 $a(Lecture Notes in Computer Science - LNCS, 5712).$v5712
520 $aMeasuring and estimating are fundamental activities for the success of any project. In the software maintenance realm the lack of maturity, or even a low level of interest in adopting effective maintenance techniques and related metrics, have been pointed out as an important cause for the high costs involved. In this paper data mining techniques are applied to provide a sound estimation for the time required to accomplish a maintenance task. Based on real world data regarding maintenance requests, some regression models are built to predict the time required for each maintenance. Data on the team skill and the maintenance characteristics are mapped into values that predict better time estimations in comparison to the one predicted by the human expert. A particular finding from this research is that the time prediction provided by a human expert works as an inductive bias that improves the overall prediction accuracy.
653 $aData mining
653 $aInformal reasoning
653 $aSoftware maintenance
700 1 $aFERNEDA, E.
700 1 $aANQUETIL, N.
700 1 $aTEIXEIRA, E. D'A.
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Embrapa Unidades Centrais (AI-SEDE) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
20/02/1995 |
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Data da última atualização: |
29/04/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CORTE, H. R.; RAMALHO, M. A. P.; GONÇALVES, F. M. A.; ABREU, A. de F. B. |
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Afiliação: |
HERCULES RENATO CORTE, UFLA; MAGNO ANTONIO PATTO RAMALHO, UFLA; FLAVIA MARIA AVELAR CONÇALVES, UFLA; ANGELA DE FATIMA BARBOSA ABREU, CNPAF. |
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Título: |
Natural selection for grain yield in dry bean populations bred by the bulk method. |
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Ano de publicação: |
2002 |
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Fonte/Imprenta: |
Euphytica, v. 123, n. 3, p. 387-393, Feb. 2002. |
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DOI: |
10.1023/A:1015065815131 |
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Idioma: |
Inglês |
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Conteúdo: |
Three dry bean harvests are possible in some regions of Brazil that differ significantly in temperature, rainfall and day length conditions. Thus in breeding programs, generation advance using the bulk method can be carried out in these three periods. It is questionable whether under conditions such as these the action of natural selection would contribute to an increased frequency of individuals considered superior by breeders. The present study assessed six segregating populations, for up to 17 successive generations to check the effects of natural selection during inbreeding. Six populations were generated from a partial diallel: one group consisting of two early maturity cultivars, ESAL 686 and Manteigão Fosco was crossed to a second group of three cultivars with medium maturity, Carioca MG, Milionario and Ouro. The six populations plus the five parents were assessed in experiments using a randomized complete block design, in three locations: Lavras, where in breeding started from the F2 generation; Lambari and Patos de Minas, from the F3 generation. A linear regression equation was fitted to the parents and hybrids mean data in each location, considering grain yield as the dependent variable (y) and generations (F2 = 1, F3 = 2, etc.) as the independent variable. Genetic progress was estimated from the differences between the linear regression coefficients of the hybrids (bi)and the mean of the b coefficient of their respective parents (bj). The (bi-bj) were positive in all cases, showing that natural selection acted in all the segregating populations and contributed to an average increase in grain yield of 2.5% per generation over the mean of the parents. MenosThree dry bean harvests are possible in some regions of Brazil that differ significantly in temperature, rainfall and day length conditions. Thus in breeding programs, generation advance using the bulk method can be carried out in these three periods. It is questionable whether under conditions such as these the action of natural selection would contribute to an increased frequency of individuals considered superior by breeders. The present study assessed six segregating populations, for up to 17 successive generations to check the effects of natural selection during inbreeding. Six populations were generated from a partial diallel: one group consisting of two early maturity cultivars, ESAL 686 and Manteigão Fosco was crossed to a second group of three cultivars with medium maturity, Carioca MG, Milionario and Ouro. The six populations plus the five parents were assessed in experiments using a randomized complete block design, in three locations: Lavras, where in breeding started from the F2 generation; Lambari and Patos de Minas, from the F3 generation. A linear regression equation was fitted to the parents and hybrids mean data in each location, considering grain yield as the dependent variable (y) and generations (F2 = 1, F3 = 2, etc.) as the independent variable. Genetic progress was estimated from the differences between the linear regression coefficients of the hybrids (bi)and the mean of the b coefficient of their respective parents (bj). The (bi-bj) were positive in ... Mostrar Tudo |
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Thesagro: |
Feijão; Grão; Melhoramento Genético Vegetal; Método; Phaseolus Vulgaris; Seleção. |
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Thesaurus NAL: |
Beans; Gene segregation; Natural selection; Plant breeding. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02513naa a2200289 a 4500
001 1199249
005 2022-04-29
008 2002 bl uuuu u00u1 u #d
024 7 $a10.1023/A:1015065815131$2DOI
100 1 $aCORTE, H. R.
245 $aNatural selection for grain yield in dry bean populations bred by the bulk method.$h[electronic resource]
260 $c2002
520 $aThree dry bean harvests are possible in some regions of Brazil that differ significantly in temperature, rainfall and day length conditions. Thus in breeding programs, generation advance using the bulk method can be carried out in these three periods. It is questionable whether under conditions such as these the action of natural selection would contribute to an increased frequency of individuals considered superior by breeders. The present study assessed six segregating populations, for up to 17 successive generations to check the effects of natural selection during inbreeding. Six populations were generated from a partial diallel: one group consisting of two early maturity cultivars, ESAL 686 and Manteigão Fosco was crossed to a second group of three cultivars with medium maturity, Carioca MG, Milionario and Ouro. The six populations plus the five parents were assessed in experiments using a randomized complete block design, in three locations: Lavras, where in breeding started from the F2 generation; Lambari and Patos de Minas, from the F3 generation. A linear regression equation was fitted to the parents and hybrids mean data in each location, considering grain yield as the dependent variable (y) and generations (F2 = 1, F3 = 2, etc.) as the independent variable. Genetic progress was estimated from the differences between the linear regression coefficients of the hybrids (bi)and the mean of the b coefficient of their respective parents (bj). The (bi-bj) were positive in all cases, showing that natural selection acted in all the segregating populations and contributed to an average increase in grain yield of 2.5% per generation over the mean of the parents.
650 $aBeans
650 $aGene segregation
650 $aNatural selection
650 $aPlant breeding
650 $aFeijão
650 $aGrão
650 $aMelhoramento Genético Vegetal
650 $aMétodo
650 $aPhaseolus Vulgaris
650 $aSeleção
700 1 $aRAMALHO, M. A. P.
700 1 $aGONÇALVES, F. M. A.
700 1 $aABREU, A. de F. B.
773 $tEuphytica$gv. 123, n. 3, p. 387-393, Feb. 2002.
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