The Experts below are selected from a list of 219 Experts worldwide ranked by ideXlab platform
Rodel D. Lasco - One of the best experts on this subject based on the ideXlab platform.
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Biomass Equations for Tropical Tree Plantation Species Using Secondary Data from the Philippines
2020Co-Authors: Ma. Regina N. Banaticla, Renezita F. Sales, Rodel D. LascoAbstract:Estimation of the magnitude of sinks and sources of carbon requires reliable estimates of the biomass of forests and of individual trees. Equations for predicting tree biomass have been developed using secondary data involving destructive sampling in plantations in several localities in the Philippines. These Equations allow estimates of carbon sequestration to be made at much lower cost than would be incurred if detailed stand inventories were undertaken. The species included in the study reported here include Gmelina arborea, Paraserianthes falcataria, Swietenia macrophylla and Dipterocarp species in Mindanao; Leucaena leucocephala from Laguna, Antique, Cebu, Iloilo, Rizal, and Ilocos Sur, and Acacia mangium, Acacia auriculiformis and G. arborea in Leyte. Non-linear regression was used to derive species-specific, site-specific and Generic Equations between yield and diameter of the form y = aDb. Equations were evaluated based on the correlation coefficient, standard error of the estimate and residual plots. Regressions resulted to high r values (>0.90). In some cases, non-homogeneous variance was encountered. The Generic Equation improved estimates compared with models used in previous studies.
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Biomass Equations for Tropical Tree Plantation Species in Young Stands Using Secondary Data from the Philippines
Annals of Tropical Research, 2007Co-Authors: Ma. Regina N. Banaticla, Renezita F. Sales, Rodel D. LascoAbstract:Estimation of the magnitude of sinks and sources of carbon requires reliable estimates of the biomass of forests and of individual trees. Equations for predicting tree biomass have been developed using secondary data involving destructive sampling in plantations (mostly less than 10 years of age) in several localities in the Philippines. These Equations allow estimates of carbon sequestration to be made at much lower cost than would be incurred if detailed stand inventories were undertaken. The species included in the study reported here include Gmelina arborea Roxb., Paraserianthes falcataria (L.) Nielsen Swietenia macrophylla King and Dipterocarp species in Mindanao, and Leucaena leucocephala de Wit from Laguna, Antique, Cebu, Iloilo, Rizal, and Ilocos Sur. Non-linear regression was used to derive species-specific, site-specific and Generic Equations between yield and diameter of the form y = D. Equations were evaluated based on the correlation coefficient, standard error of estimate and residual plots. Regressions resulted in high r values (>0.90). In some cases, non-homogeneous variance was encountered. The Generic Equation improved estimates compared with models used in previous studies.
Izzet Duyar - One of the best experts on this subject based on the ideXlab platform.
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Piecewise regression Equations for estimating stature: an anthropometric study in Spanish females
International Journal of Legal Medicine, 2020Co-Authors: Gonzalo Saco-ledo, Jordi Porta, Tesla A. Monson, Marianne F. Brasil, Derya Atamtürk, Izzet DuyarAbstract:In forensic anthropology, Generic Equations are generally preferred for estimation of stature. However, recent studies have demonstrated that regression Equations specific to stature groups yield more accurate predictions. Almost all previous studies have been conducted on male subjects, and it is not currently known how well such Equations work for females. Therefore, this study aims to test whether regression Equations specific to stature groups work for females as well. To this end, a cross-sectional study was conducted to estimate stature on a sample of 351 Spanish adult females. The participants were randomized into a calibration group ( n = 185) and a validation group ( n = 166). Equations for stature estimation based on tibial length were developed in the calibration group, which was categorized according to stature (short, medium, and tall) using the 15th and 85th percentiles as cut-off points. The standard errors of the estimations (SEEs) for the group-specific regression Equations (SEE = 2.35–2.66 cm) were lower than for the general formula derived for all participants of the calibration group (SEE = 3.46 cm). The specific Equations resulted in smaller differences between estimated and recorded statures than the Generic Equation when we tested the Equations with the validation group. Additionally, the SEE values of the stature-specific Equations are lower compared to Generic Equations applied to other human populations. In conclusion, the group-specific Equations from tibial length have high accuracy compared with previously derived Equations for Spanish females and other populations. This procedure for estimating stature thereby improves the tools available to forensic scientists.
E. Díaz-dorado - One of the best experts on this subject based on the ideXlab platform.
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Review of power curve modelling for windturbines
Renewable and Sustainable Energy Reviews, 2013Co-Authors: C. Carrillo, A. F. Obando Montaño, J. Cidrás, E. Díaz-doradoAbstract:Currently, variable speed wind turbine generators (VSWTs) are the type of wind turbines most widely installed. For wind energy studies, they are usually modelled by means the approximation of the manufacturer power curve using a Generic Equation. In literature, several expressions to do this approximation can be found; nevertheless, there is not much information about which is the most appropriate to represent the energy produced by a VSWT. For this reason, in this paper, it is carried out a review of the Equations commonly used to represent the power curves of VSWTs: polynomial power curve, exponential power curve, cubic power curve and approximate cubic power curve. They have been compared to manufacturer power curves by using the coefficients of determination, as fitness indicators, and by using the estimation of energy production. Data gathered from nearly 200 commercial VSWTs, ranging from 225 to 7500 kW, has been used for this analysis. Results of the analysis presented in the paper show that exponential and cubic approximations give the higher R2values and the lower error in energy estimation. With the approximate cubic power curve quite high values of R2and low errors in energy estimation are achieved, which makes this kind of approximation very interesting due to its simplicity. Finally, the polynomial power curve shows the worst results mainly due to its sensitivity to the data given by the manufacturer. © 2013 Elsevier Ltd.
Ma. Regina N. Banaticla - One of the best experts on this subject based on the ideXlab platform.
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Biomass Equations for Tropical Tree Plantation Species Using Secondary Data from the Philippines
2020Co-Authors: Ma. Regina N. Banaticla, Renezita F. Sales, Rodel D. LascoAbstract:Estimation of the magnitude of sinks and sources of carbon requires reliable estimates of the biomass of forests and of individual trees. Equations for predicting tree biomass have been developed using secondary data involving destructive sampling in plantations in several localities in the Philippines. These Equations allow estimates of carbon sequestration to be made at much lower cost than would be incurred if detailed stand inventories were undertaken. The species included in the study reported here include Gmelina arborea, Paraserianthes falcataria, Swietenia macrophylla and Dipterocarp species in Mindanao; Leucaena leucocephala from Laguna, Antique, Cebu, Iloilo, Rizal, and Ilocos Sur, and Acacia mangium, Acacia auriculiformis and G. arborea in Leyte. Non-linear regression was used to derive species-specific, site-specific and Generic Equations between yield and diameter of the form y = aDb. Equations were evaluated based on the correlation coefficient, standard error of the estimate and residual plots. Regressions resulted to high r values (>0.90). In some cases, non-homogeneous variance was encountered. The Generic Equation improved estimates compared with models used in previous studies.
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Biomass Equations for Tropical Tree Plantation Species in Young Stands Using Secondary Data from the Philippines
Annals of Tropical Research, 2007Co-Authors: Ma. Regina N. Banaticla, Renezita F. Sales, Rodel D. LascoAbstract:Estimation of the magnitude of sinks and sources of carbon requires reliable estimates of the biomass of forests and of individual trees. Equations for predicting tree biomass have been developed using secondary data involving destructive sampling in plantations (mostly less than 10 years of age) in several localities in the Philippines. These Equations allow estimates of carbon sequestration to be made at much lower cost than would be incurred if detailed stand inventories were undertaken. The species included in the study reported here include Gmelina arborea Roxb., Paraserianthes falcataria (L.) Nielsen Swietenia macrophylla King and Dipterocarp species in Mindanao, and Leucaena leucocephala de Wit from Laguna, Antique, Cebu, Iloilo, Rizal, and Ilocos Sur. Non-linear regression was used to derive species-specific, site-specific and Generic Equations between yield and diameter of the form y = D. Equations were evaluated based on the correlation coefficient, standard error of estimate and residual plots. Regressions resulted in high r values (>0.90). In some cases, non-homogeneous variance was encountered. The Generic Equation improved estimates compared with models used in previous studies.
Gonzalo Saco-ledo - One of the best experts on this subject based on the ideXlab platform.
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Piecewise regression Equations for estimating stature: an anthropometric study in Spanish females
International Journal of Legal Medicine, 2020Co-Authors: Gonzalo Saco-ledo, Jordi Porta, Tesla A. Monson, Marianne F. Brasil, Derya Atamtürk, Izzet DuyarAbstract:In forensic anthropology, Generic Equations are generally preferred for estimation of stature. However, recent studies have demonstrated that regression Equations specific to stature groups yield more accurate predictions. Almost all previous studies have been conducted on male subjects, and it is not currently known how well such Equations work for females. Therefore, this study aims to test whether regression Equations specific to stature groups work for females as well. To this end, a cross-sectional study was conducted to estimate stature on a sample of 351 Spanish adult females. The participants were randomized into a calibration group ( n = 185) and a validation group ( n = 166). Equations for stature estimation based on tibial length were developed in the calibration group, which was categorized according to stature (short, medium, and tall) using the 15th and 85th percentiles as cut-off points. The standard errors of the estimations (SEEs) for the group-specific regression Equations (SEE = 2.35–2.66 cm) were lower than for the general formula derived for all participants of the calibration group (SEE = 3.46 cm). The specific Equations resulted in smaller differences between estimated and recorded statures than the Generic Equation when we tested the Equations with the validation group. Additionally, the SEE values of the stature-specific Equations are lower compared to Generic Equations applied to other human populations. In conclusion, the group-specific Equations from tibial length have high accuracy compared with previously derived Equations for Spanish females and other populations. This procedure for estimating stature thereby improves the tools available to forensic scientists.