956 resultados para equação de predição


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Foram avaliados os ganhos totais preditos por diferentes critérios de seleção, em seis características de crescimento em famílias de meios-irmãos de Eucalyptus camaldulensis. A situação simulada consistiu na seleção de 25% das 44 famílias estudadas, e de 17% das plantas dentro dessas famílias, proporcionando, assim, uma seleção de 4,25% dos indivíduos constantes do ensaio. Os critérios de seleção empregados foram: seleção direta e indireta; índice clássico de Smith & Hazel, com quatro pesos econômicos, e índice de Pesek & Baker, em três situações. Os critérios de seleção utilizados mostraram-se semelhantes entre si, com ligeira superioridade do índice clássico quando se estabeleceu como vetor de pesos econômicos o coeficiente de variação genética associado a cada uma das características analisadas.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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O consumo de matéria seca (CMS) do capim tanzânia de 24 vacas lactantes mestiças (HPB x Gir) e Gir, sob pastejo, foi estimado no mês de janeiro de 1998, a partir da relação entre a digestibilidade da MS da forragem e a produção fecal obtida com auxílio do cromo mordente por meio de um modelo não-linear. Os resultados do consumo estimado foram comparados aos consumos preditos por diferentes equações baseadas nos dados de degradabilidade do capim, no rúmen. A pastagem foi manejada com taxa de lotação de dois animais/ha, em sistema de pastejo rotativo com três dias de ocupação do piquete e 39 dias de descanso. Foram utilizadas para predizer o CMS diferentes equações: CMS = -1,19 + 0,035 (a+ b) + 28,5c (1), CMS = -0,822 + 0,0748 (a+ b) + 40,7c (2), CMS = -8,286 + 0,266a + 0,102b +17,696c (3) e CMS = [%FDN na MS]* [consumo de FDN ] / [(1-a-b)/K P +b/(c+ k p)]/24] (4). As equações, em geral, subestimaram o consumo obtido no modelo não-linear (9,6 kg/vaca/dia). Os consumos médios de capim de 6,2 e 6,0 kg MS/vaca/dia obtidas, respectivamente, nas equações de (2) e (4) foram semelhantes entre si e inferiores ao das equações de (1) (12,7 kg/vaca/dia) e (3) (8,1 kg/vaca/dia). A predição do consumo de forrageiras tropicais, sob pastejo, utilizando-se as equações baseadas nas variáveis da degradação in situ, constitui um importante potencial para estas avaliações. Entretanto, mais estudos dessa natureza devem ser realizados para validar o uso destas equações na prática.

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Foram desenvolvidas equações de predição de consumo de pasto de capim-elefante (Pennisetum purpureum, Schumack) por vacas mestiças Holandês x Zebu em lactação, utilizando-se procedimentos de stepwise em regressões múltiplas, aplicados a um banco de dados de experimentos conduzidos ao longo de três anos na Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Gado de Leite (Coronel Pacheco, MG). As variáveis independentes disponíveis foram relacionadas a características inerentes às vacas (dias em lactação; teores de proteína, gordura e extrato seco total e produções destes componentes no leite; produção de leite in natura ou corrigida para 4% de gordura; ordem de lactação; peso vivo atual; peso vivo ao parto e grau de sangue Holandês x Zebu); ao manejo (dias de pastejo; disponibilidade de forragem e período de descanso da pastagem); ao ambiente (estação do ano e precipitação pluviométrica) e à alimentação (digestibilidade in vitro e parâmetros da composição química do pasto de capim-elefante e da cana-de-açúcar - Saccharum officinarum (L.) corrigida com 1% de uréia; consumos de suplemento volumoso (cana corrigida com uréia) e concentrado; concentrações fecais de proteína bruta e de fibras em detergente neutro e ácido). Efeitos linear e quadrático e transformações logarítmicas foram adicionalmente incluídos no banco de dados. Foram obtidas equações de predição de consumo de pasto de capim-elefante (expresso em kg/vaca/dia ou % do peso vivo) com coeficientes de determinação de 65,2 a 67,0%. As principais variáveis independentes incluídas nas equações foram o consumo do suplemento volumoso usado na estação seca do ano (cana corrigida com uréia); a digestibilidade in vitro do pasto de capim-elefante; a precipitação pluviométrica; a produção de leite corrigida para 4% de gordura; o peso vivo atual ou, em alternativa a este, o valor da pesagem realizada após o parto da vaca; além do consumo de suplemento concentrado, que evidenciou um efeito de substituição àquele do pasto de capim-elefante.

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O consumo de matéria seca (CMS) do capim-coastcross, sob pastejo, de vacas lactantes mestiças (HPB x Gir) e Gir, foi calculado a partir da relação entre a digestibilidade in vitro da MS (DIVMS) da forragem (extrusa colhida com animais esôfago- fistulados) e a produção fecal obtida com auxílio do cromo mordante por meio de um modelo não-linear. A pastagem foi manejada com uma taxa de lotação de 1,6 e 3,2 animais/ha, respectivamente para as épocas seca e chuvosa do ano, num sistema de pastejo rotativo com três dias de ocupação e 27 dias de descanso. Quatro diferentes equações baseadas em variáveis de degradação ruminal foram utilizadas para predizer o consumo de MS: CMS = -1,19 + 0,035 (a+ b) + 28,5c (1), CMS = -0,822 + 0,0748 (a+ b) + 40,7c (2), CMS = -8,286 + 0,266a + 0,102b +17,696c (3) e CMS = [%FDN na MS]* [consumo de FDN ] / [(1-a-b)/K P +b/(c+ k p)]/24] (4). Os dados observados utilizando as equações 1 e 2 (12,2 e 12,7 kg/vaca/dia respectivamente) foram similares entre si e superiores aos resultados obtidos na equação 4 (7,8 kg/vaca/dia). Já o resultado obtido pela equação 3 (5,5 kg/vaca/dia) foi menor do que aqueles determinados pelas outras equações, subestimando o CMS calculado a partir do cromo mordante (6,3 kg/vaca/dia). A predição do consumo de forrageiras tropicais sob pastejo, utilizando equações baseadas nas variáveis de degradação, constitui um importante potencial para estas avaliações. Entretanto, mais estudos devem ser realizados antes de se usarem estas equações na prática.

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Objetivou-se avaliar as equações para predição das exigências protéicas de matrizes pesadas em crescimento, desenvolvidas em estudos anteriores na Faculdade de Ciências Agrárias e Veterinárias da UNESP, Jaboticabal, tendo como padrão de comparação as recomendações estabelecidas pelo manual de criação da linhagem. Foram utilizadas 288 matrizes pesadas da linhagem Hubbard Hy-Yield, com cinco semanas de idade, em delineamento inteiramente casualizado, com dois tratamentos e seis repetições, sendo 24 aves por unidade experimental até 14 semanas e, de 15 a 20 semanas de idade, 20 aves por unidade experimental. Um tratamento foi representado pelas recomendações protéicas para a linhagem (testemunha) e o outro pelas seguintes equações de predição das exigências de proteína: de 5 a 8 semanas PB (g/ave/dia) = 2,02.P0,75+ 0,350.G, 9 a 14 semanas - PB = 2,02.P0,75 + 0,406.G e de 15 a 20 semanas PB = 2,02.P0,75 + 0,463.G, em que P é o peso corporal (kg) e G, o ganho de peso diário (g). Os resultados indicaram que as equações de predição para proteína, apesar de não comprometerem o peso ou a uniformidade corporal em relação ao tratamento testemunha, determinaram menor porcentagem de peito e maior de gordura abdominal e maior teor de gordura na carcaça, sendo atribuído à menor ingestão de proteína proporcionada pelas equações de predição e, conseqüentemente, deficiência em relação a alguns aminoácidos que não foram suplementados.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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O objetivo do trabalho foi elaborar um modelo para estimar as exigências de proteína bruta (PB) para poedeiras leves, usando o método fatorial. Para determinar as exigências de proteína bruta (PB) para manutenção foi utilizada a técnica do balanço de nitrogênio. A exigência de proteína bruta para o ganho de peso foi determinada em função do conteúdo de nitrogênio na carcaça e a eficiência de utilização do nitrogênio da dieta. A exigência de PB, para produção de ovos, foi determinada considerando o teor de PB determinado nos ovos e a eficiência de deposição do nitrogênio no ovo. A partir dos valores das exigências para manutenção, para o ganho e produção foi elaborada uma equação para predizer as exigências diárias de PB (g/ ave/ dia) para poedeiras: PB = 1,94. P0,75 + 0,48.G + 0,301.O, em que P = peso corporal (kg), G = ganho de peso diário (g/dia) e O = massa de ovos produzida (g/ave/dia).

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A 2.5D ray-tracing propagation model is proposed to predict radio loss in indoor environment. Specifically, we opted for the Shooting and Bouncing Rays (SBR) method, together with the Geometrieal Theory of Diffrartion (GTD). Besides the line-of-sight propagation (LOS), we consider that the radio waves may experience reflection, refraction, and diffraction (NLOS). In the Shooting and Bouncing Rays (SBR) method, the transmitter antenna launches a bundle of rays that may or may not reach the receiver. Considering the transmitting antenna as a point, the rays will start to launch from this position and can reach the receiver either directly or after reflections, refractions, diffractions, or even after any combination of the previous effects. To model the environment, a database is built to record geometrical characteristics and information on the constituent materials of the scenario. The database works independently of the simulation program, allowing robustness and flexibility to model other seenarios. Each propagation mechanism is treated separately. In line-of-sight propagation, the main contribution to the received signal comes from the direct ray, while reflected, refracted, and diffracted signal dominate when the line-of-sight is blocked. For this case, the transmitted signal reaches the receiver through more than one path, resulting in a multipath fading. The transmitting channel of a mobile system is simulated by moving either the transmitter or the receiver around the environment. The validity of the method is verified through simulations and measurements. The computed path losses are compared with the measured values at 1.8 GHz ftequency. The results were obtained for the main corridor and room classes adjacent to it. A reasonable agreement is observed. The numerical predictions are also compared with published data at 900 MHz and 2.44 GHz frequencies showing good convergence

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The telecommunications industry has experienced recent changes, due to increasing quest for access to digital services for data, video and multimedia, especially using the mobile phone networks. Recently in Brazil, mobile operators are upgrading their networks to third generations systems (3G) providing to users broadband services such as video conferencing, Internet, digital TV and more. These new networks that provides mobility and high data rates has allowed the development of new market concepts. Currently the market is focused on the expansion of WiMAX technology, which is gaining increasingly the market for mobile voice and data. In Brazil, the commercial interest for this technology appears to the first award of licenses in the 3.5 GHz band. In February 2003 ANATEL held the 003/2002/SPV-ANATEL bidding, where it offered blocks of frequencies in the range of 3.5 GHz. The enterprises who purchased blocks of frequency were: Embratel, Brazil Telecom (Vant), Grupo Sinos, Neovia and WKVE, each one with operations spread in some regions of Brazil. For this and other wireless communications systems are implemented effectively, many efforts have been invested in attempts to developing simulation methods for coverage prediction that is close to reality as much as possible so that they may become believers and indispensable tools to design wireless communications systems. In this work wasm developed a genetic algorithm (GA's) that is able to optimize the models for predicting propagation loss at applicable frequency range of 3.5 GHz, thus enabling an estimate of the signal closer to reality to avoid significant errors in planning and implementation a system of wireless communication

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The development of wireless telecommunication in the last years has been great. It has been taking academics to conceive new ideas and techniques. Their aims are to increase the capacity and the quality of the system s services. Cells that are smaller every time, frequencies that are every time higher and environments that get more and more complex, all those facts deserve more accurate models the propagation prediction techniques are inserted in this context and results with a merger of error that is compatible with the next generations of communication systems. The objective of this Work is to present results of a propagation measurement campaign, aiming at pointing the characteristics of the mobile systems covering in the city of Natal (state of Rio Grande do Norte, Brazil). A mobile laboratory was set up, using the infra-structure available and frequently used by ANATEL. The measures were taken in three different areas: one characterized by high buildings, high relief, presence of trees and towers of different highs. These areas covered the city s central zone, a suburban / rural zone and a section of coast surrounded by sand dunes. It is important to highlight that the analysis was made taking into consideration the actual reality of cellular systems with covering ranges by reduced cells, with the intent of causing greater re-use of frequencies and greater capacity of telephone traffic. The predominance of telephone traffic by cell in the city of Natal occurs within a range inferior to 3 (three) km from the Radio-Base Station. The frequency band used was 800 MHz, corresponding to the control channels of the respective sites, which adopt the FSK modulation technique. This Dissertation starts by presenting a general vision of the models used for predicting propagation. Then, there is a description of the methodology used in the measuring, which were done using the same channels of control of the cellular system. The results obtained were compared with many existing prediction models, and some adaptations were developed by using regression techniques trying to obtain the most optimized solutions. Furthermore, according to regulations from the old Brazilian Holding Telebrás, a minimum covering of 90% of a determined previously area, in 90% of the time, must be obeyed when implanting cellular systems. For such value to be reached, considerations and studies involving the specific environment that is being covered are important. The objective of this work is contribute to this aspect

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One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

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A serious problem that affects an oil refinery s processing units is the deposition of solid particles or the fouling on the equipments. These residues are naturally present on the oil or are by-products of chemical reactions during its transport. A fouled heat exchanger loses its capacity to adequately heat the oil, needing to be shut down periodically for cleaning. Previous knowledge of the best period to shut down the exchanger may improve the energetic and production efficiency of the plant. In this work we develop a system to predict the fouling on a heat exchanger from the Potiguar Clara Camarão Refinery, based on data collected in a partnership with Petrobras. Recurrent Neural Networks are used to predict the heat exchanger s flow in future time. This variable is the main indicator of fouling, because its value decreases gradually as the deposits on the tubes reduce their diameter. The prediction could be used to tell when the flow will have decreased under an acceptable value, indicating when the exchanger shutdown for cleaning will be needed

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This work aims to determine a better methodology to help predicting some operational parameters to a new design of mixer-settler on treating wastewater produced by petroleum industry, called MDIF (Misturador-Decantador à Inversão de Fases/ Mixer-Settler based on Phase Inversion MSPI). The data from this research were obtained from the wastewater treatment unit, called MSPI-TU, installed on a wastewater treatment plant (WTP) of PETROBRAS/UO-RNCE. The importance in determining the better methodology to predict the results of separation and extraction efficiency of the equipment, contributes significantly to determine the optimum operating variables for the control of the unit. The study was based on a comparison among the experimental efficiency (E) obtained by operating MSPI-TU, the efficiency obtained by experimental design equation (Eplan) from the software Statistica Experimental Design® (version 7.0), and the other obtained from a modeling equation based on a dimensional analysis (Ecalc). The results shows that the experimental design equation gives a good prediction of the unit efficiencies with better data reliability, regarding to the condition before a run operation. The average deviation between the proposed by statistic planning model equation and experimental data was 0.13%. On the other hand, the efficiency calculated by the equation which represents the dimensional analysis, may result on important relative deviations (up 70%). Thus, the experimental design is confirmed as a reliable tool, with regard the experimental data processing of the MSPI-TU

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Eutrophication has been listed as one of the main problems of water pollution on a global level. In the Brazilian semi-arid areas this problem takes even greater proportions due to characteristical water scarcity of the region. It is extremely important to the predictive eutrophication models development and to the reservoirs management in the semi-arid region, studies that promotes understanding of the mechanisms responsible for the expansion and control of algae blooms, essential for improving the water quality of these environments. The present study had as its main aims, evaluate the temporal pattern of trophic state, considering the influence of nutrients (N and P) and the light availability in the water column in the development of phytoplankton biomass, and perform the mathematical modelling of changes in phosphorus and chlorophyll a concentrations in the Cruzeta man-made lake located on Seridó, a typical semi-arid region of Rio Grande do Norte. To this, a fortnightly monitoring was performed in the reservoir in 05 stations over the months of March 2007 to May 2008. Were measured the concentrations of total phosphorus, total organic nitrogen, chlorophyll a, total, fixed and volatile suspended solids, as well as the measure of transparency (Secchi) and the profiles of photosynthetic active radiation (PAR), temperature, pH, dissolved oxygen and electrical conductivity in the water column. Measurements of vertical profiles have shown some periods of chemical and thermal stratification, especially in the rainy season, due to increased water column depth, however, the reservoir can be classified as warm polimitic. During the study period the reservoir was characterized as eutrophic considering the concentrations of phosphorus and most of the time as mesotrophic, based on the concentrations of chlorophyll a, according to the Thornton & Rast (1993) classification. The N:P relations suggest N limitation, conversely, significant linear relationship between the algae biomass and nutrients (N and P) were not observed in our study. However, a relevant event was the negative and significant correlation presented by Kt and chlorophyll a (r ² = 0.83) at the end of the drought of 2007 and the rainy season of 2008, and the algal biomass collapse observed at the end of the drought season (Dec/07). The equation used to simulate the change in the total phosphorus was not satisfactory, being necessary inclusion of parameters able to increase the power of the model prediction. The chlorophyll a simulation presented a good adjustment trend, however there is a need to check the calibrated model parameters and subsequent equation validation