Search results for "Series"
showing 10 items of 1193 documents
Thermodynamic and kinetic aspects of the transport of small molecules in dispersed systems
1998
Abstract The knowledge of the behaviour of flavour compounds in complex multiphase systems with regard to their structure is of great importance in flavour perception of foods. The thermodynamic and kinetic behaviour of three selected flavour compounds belonging to a homologous series of esters, e.g. ethyl acetate, ethyl butanoate and ethyl hexanoate, were studied in simple and multiphase systems. The liquid system was composed of water (with or without sodium caseinate) and/or a lipid, Miglyol. First, the properties of the solutes were determined by means of their liquid–liquid partition at equilibrium and their diffusion in aqueous or lipid phases. This first step allowed to reveal the im…
Arbitrarily shaped plates analysis via Line Element-Less Method (LEM)
2018
Abstract An innovative procedure is introduced for the analysis of arbitrarily shaped thin plates with various boundary conditions and under generic transverse loading conditions. Framed into Line Element-less Method, a truly meshfree method, this novel approach yields the solution in terms of the deflection function in a straightforward manner, without resorting to any discretization, neither in the domain nor on the boundary. Specifically, expressing the deflection function through a series expansion in terms of harmonic polynomials, it is shown that the proposed method requires only the evaluation of line integrals along the boundary parametric equation. Further, minimization of appropri…
Rectilinear evolution in arvicoline rodents and numerical dating of Iberian Early Pleistocene sites
2014
Abstract Lozano-Fernandez et al. (2013a) have recently published a method intended for numerical dating of Early Pleistocene sites, which is based on the assumption of uniform, constant rate increase through time of mean lower molar tooth length of water voles ( Mimomys savini ) in a number of levels sampled in the stratigraphic sequence of Atapuerca TD site. They suggest that the regression equation obtained in this local section for site chronology on tooth size could be useful for estimating the numerical age of other localities from southwestern Europe. However, in our opinion this biostratigraphic approach has severe conceptual and methodological problems, which discourage its use as a…
Ten years surface-atmosphere water budget from the ISAC micrometeorological base in Salento peninsula and comments on the aquifer balance
2016
Data from a ten years (2003-2013) period of activity of the ISAC-Lecce micrometeorological station have been discussed focusing on the atmosphere-surface exchange. Some suitable indices have been calculated such as the precipitation intensity, the aridity index and the ground water infiltration fraction (ratio of the difference between precipitation and real evapotranspiration and the precipitation). Possible trends of annual averages in the decadal period are considered, trying to take also into account the statistical uncertainty associated to measurement errors and missing data. The results indicate a significant increasing in the precipitation intensity together with an experimental evi…
Localization Operators and an Uncertainty Principle for the Discrete Short Time Fourier Transform
2014
Localization operators in the discrete setting are used to obtain information on a signalffrom the knowledge on the support of its short time Fourier transform. In particular, the extremal functions of the uncertainty principle for the discrete short time Fourier transform are characterized and their connection with functions that generate a time-frequency basis is studied.
A new approach to portfolio selection based on forecasting
2023
In this paper we analyze the portfolio selection problem from a novel perspective based on the analysis and prediction of the time series corresponding to the portfolio’s value. Namely, we define the value of a particular portfolio at the time of its acquisition. Using the time series of historical prices of the different financial assets, we calculate backward the value that said portfolio would have had in past time periods. A damped trend model is then used to analyze this time series and to predict the future values of the portfolio, providing estimates of the mean and variance for different forecasting horizons. These measures are used to formulate the portfolio selection problem, whic…
Exploiting deep learning algorithms and satellite image time series for deforestation prediction
2022
In recent years, we have witnessed the emergence of Deep Learning (DL) methods, which have led to enormous progress in various fields such as automotive driving, computer vision, medicine, finances, and remote sensing data analysis. The success of these machine learning methods is due to the ever-increasing availability of large amounts of information and the computational power of computers. In the field of remote sensing, we now have considerable volumes of satellite images thanks to the large number of Earth Observation (EO) satellites orbiting the planet. With the revisit time of satellites over an area becoming shorter and shorter, it will probably soon be possible to obtain daily imag…
A new method for optimal synthesis of wavelet-based neural networks suitable for identification purposes
1999
Abstract This paper deals with a new method for optimal synthesis of Wavelet-Based Neural Networks (WBNN) suitable for identification purposes. The method uses a genetic algorithm (GA) combined with a steepest descent technique and least square techniques for both optimal selection of the structure of the WBNN and its training. The method is applied for designing a predictor for a chaotic temporal series
Two-level branch prediction using neural networks
2003
Dynamic branch prediction in high-performance processors is a specific instance of a general time series prediction problem that occurs in many areas of science. Most branch prediction research focuses on two-level adaptive branch prediction techniques, a very specific solution to the branch prediction problem. An alternative approach is to look to other application areas and fields for novel solutions to the problem. In this paper, we examine the application of neural networks to dynamic branch prediction. We retain the first level history register of conventional two-level predictors and replace the second level PHT with a neural network. Two neural networks are considered: a learning vec…
Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators
2021
One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…