985 resultados para Partial oxalate method
Resumo:
The paper has been presented at the 12th International Conference on Applications of Computer Algebra, Varna, Bulgaria, June, 2006
Resumo:
Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.
Resumo:
A group-theoretic method of obtaining more general class of generating functions from a given class of partial quasi-bilateral generating functions involving Hermite, Laguerre and Gegenbaur polynomials are discussed.
Resumo:
A new creep test, Partial Triaxial Test (PTT), was developed to study the permanent deformation properties of asphalt mixtures. The PTT used two duplicate platens whose diameters were smaller than the diameter of the cylindrical asphalt mixtures specimen. One base platen was centrally placed under the specimen and another loading platen was centrally placed on the top surface of the specimen. Then the compressive repeated load was applied on the loading platen and the vertical deformation of the asphalt mixture was recorded in the PTTs. Triaxial repeated load permanent deformation tests (TRT) and PTTs were respectively conducted on AC20 and SMA13 asphalt mixtures at 40°C and 60°C so as to provide the parameters of the creep constitutive relations in the ABAQUS finite element models (FEMs) which were built to simulate the laboratory wheel tracking tests. The real laboratory wheel tracking tests were also conducted on AC20 and SMA13 asphalt mixtures at 40°C and 60°C. Then the calculated rutting depth from the FEMs were compared with the measured rutting depth of the laboratory wheeling tracking tests. Results indicated that PTT was able to characterize the permanent deformation of the asphalt mixtures in laboratory. The rutting depth calculated using the parameters estimated from PTTs' results was closer to and showed better matches with the measured rutting than the rutting depth calculated using the parameters estimated from TRTs' results. Main reason was that PTT could better simulate the changing confinement conditions of asphalt mixtures in the laboratory wheeling tracking tests than the TRT.
Resumo:
A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.
Resumo:
Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.
Resumo:
2010 Mathematics Subject Classification: 74J30, 34L30.
Resumo:
An algorithm is produced for the symbolic solving of systems of partial differential equations by means of multivariate Laplace–Carson transform. A system of K equations with M as the greatest order of partial derivatives and right-hand parts of a special type is considered. Initial conditions are input. As a result of a Laplace–Carson transform of the system according to initial condition we obtain an algebraic system of equations. A method to obtain compatibility conditions is discussed.
Resumo:
This paper presents a methodology to emulate Single Event Upsets (SEUs) in FPGA flip-flops (FFs). Since the content of a FF is not modifiable through the FPGA configuration memory bits, a dedicated design is required for fault injection in the FFs. The method proposed in this paper is a hybrid approach that combines FPGA partial reconfiguration and extra logic added to the circuit under test, without modifying its operation. This approach has been integrated into a fault-injection platform, named NESSY (Non intrusive ErrorS injection SYstem), developed by our research group. Finally, this paper includes results on a Virtex-5 FPGA demonstrating the validity of the method on the ITC’99 benchmark set and a Feed-Forward Equalization (FFE) filter. In comparison with other approaches in the literature, this methodology reduces the resource consumption introduced to carry out the fault injection in FFs, at the cost of adding very little time overhead (1.6 �μs per fault).
Resumo:
When we study the variables that a ffect survival time, we usually estimate their eff ects by the Cox regression model. In biomedical research, e ffects of the covariates are often modi ed by a biomarker variable. This leads to covariates-biomarker interactions. Here biomarker is an objective measurement of the patient characteristics at baseline. Liu et al. (2015) has built up a local partial likelihood bootstrap model to estimate and test this interaction e ffect of covariates and biomarker, but the R code developed by Liu et al. (2015) can only handle one variable and one interaction term and can not t the model with adjustment to nuisance variables. In this project, we expand the model to allow adjustment to nuisance variables, expand the R code to take any chosen interaction terms, and we set up many parameters for users to customize their research. We also build up an R package called "lplb" to integrate the complex computations into a simple interface. We conduct numerical simulation to show that the new method has excellent fi nite sample properties under both the null and alternative hypothesis. We also applied the method to analyze data from a prostate cancer clinical trial with acid phosphatase (AP) biomarker.
Resumo:
This text is a first that the author would develop later. It is illustrated with case studies and original terminology. It begins with a brief conceptual contribution on the difference in approach between the German and French geographical schools, and continues with a reflection on the historical and geographical relativity of the boundary. Subsequently, at its greatest extent, the article provides a taxonomy of states: amorphous states, in three cases, that of the "savage peoples" without boundaries, of black Africa; that of semi-civilized peoples of northwest Africa, and the particular case of European civilized nomads, called ―terranovas‖. Framed states, with borders undergoing processes of emergence or extension, especially the case of Yugoslavia. And, in addition, some references to stable boundaries of Albania and the Netherlands
Resumo:
Future teachers must be competent in creating educational settings, which provide tools to their students future they can develop a conscious mind, able to interpret their experiences, to make decisions and imagine innovative solutions to help you participate autonomously and responsible in society. This requires an educational system that allows them to integrate the subjective into a broader spatial and temporal context. La patrimonializatión of “Cultural artefacts” and oral history, the basis of which, are found in the active mind and links both the personal and the group experience, don’t only serve as a catalyst to achieving this goal, but rather, they facilitate the implementation of established practice in infant education. To gain this experience we offer the opportunity for students of their degree in Infant Education in the Public University of Navarre, training within the framework of social didactics, allowing students to learn about established practice from iconic, materials and oral sources in the Archive of Intangible Cultural Heritage of Navarra. The vidences points to their effectiveness and presented in a work in progress.
Resumo:
In this article we consider the development of discontinuous Galerkin finite element methods for the numerical approximation of the compressible Navier-Stokes equations. For the discretization of the leading order terms, we propose employing the generalization of the symmetric version of the interior penalty method, originally developed for the numerical approximation of linear self-adjoint second-order elliptic partial differential equations. In order to solve the resulting system of nonlinear equations, we exploit a (damped) Newton-GMRES algorithm. Numerical experiments demonstrating the practical performance of the proposed discontinuous Galerkin method with higher-order polynomials are presented.
Resumo:
High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).
Resumo:
Pseudokirchneriella subcapitata is a unicellular green algae widely distributed in freshwater and soils. Due to its cosmopolitan characteristic, its use is recommended by national and international protocols in ecotoxicity studies. The alteration of phosphatase activities by agriculture pollutants like heavy metals has been extensively used as a biomarker in risk assessment and biomonitoring. In this study, we compared the extraction of acid phosphatase from P. subcapitata by different procedures and we studied the stability, substrates specificity, kinetics and the effect of Hg2+ in the crude extract. The freezing and thawing technique associated with probe sonication was the most suitable method of extraction. The enzyme was stable when frozen at -20ºC for at least six months, showed an optimum pH of 5 and a Km value of 0.27 mM for p-nitrophenylphosphate (pNPP) as substrate. Some natural organic substrates were cleaved by a similar extent as the synthetic substrate pNPP. Short term exposure (24 hours) to Hg2+ had little effect but inhibition of the specific activity was observed after 7 days with EC50 (concentration of Hg2+ that promotes 50% decrease of specific activity) value of 12.63 μM Hg2+ .