Search results for "Modelli"

Mathematical modeling and parameters estimation of a car crash using data-based regressive model approach

2011

Author's version of an article in the journal: Applied Mathematical Modelling. Also available from the publisher at: http://dx.doi.org/10.1016/j.apm.2011.04.024 n this paper we present the application of regressive models to simulation of car-to-pole impacts. Three models were investigated: RARMAX, ARMAX and AR. Their suitability to estimate physical system parameters as well as to reproduce car kinematics was examined. It was found out that they not only estimate the one quantity which was used for their creation (car acceleration) but also describe the car's acceleration, velocity and crush. A virtual experiment was performed to obtain another set of data for use in further research. An A…

Forward and backward diffusion approximations for haploid exchangeable population models

2001

Abstract The class of haploid population models with non-overlapping generations and fixed population size N is considered such that the family sizes ν1,…,νN within a generation are exchangeable random variables. A criterion for weak convergence in the Skorohod sense is established for a properly time- and space-scaled process counting the number of descendants forward in time. The generator A of the limit process X is constructed using the joint moments of the offspring variables ν1,…,νN. In particular, the Wright–Fisher diffusion with generator Af(x)= 1 2 x(1−x)f″(x) appears in the limit as the population size N tends to infinity if and only if the condition lim N→∞ E((ν 1 −1) 3 )/(N Var …

Sviluppi recenti e nuove tecnologie per la stima dei fabbisogni irrigui in ambiente mediterraneo

2008

B-0-(B)over-bar(0) mixing and decay constants with the non-perturbatively improved action

2001

Several quantities relevant to phenomenological studies of B-0-(B) over bar (0) mixing are computed on the lattice. Our main results are f(Bd) root(B) over cap (Bd) = 206(28) (14)(-00)(+31) MeV, xi = f(Bd) root(B) over capB(x)/f(Bd) root(B) over cap (Bd) = 1.16(7). We also obtain the related quantities f(Bs) root(B) over cap (Bs) - 237(18) (10)(-00)(+34) MeV, f(Bd) = 174(22)(-0-0-00)(+7+5+26) MeV, f(Bs) = 204(15)(-0-0-00)(+7+4+31) MeV, f(Bs)/f(Bd) = 1.17(4)(-1)(+0), f(Bd)/f(Ds) = 0.74(5). After combining our results with the experimental world average Deltam(d)((exp)), we predict Deltam(s) = 15.8(2.1)(3.3) ps(-1). We have also computed the relevant parameters for D-0-(D) over bar (0) mixing…

Numerical stochastic perturbation theory in the Schrödinger functional

2013

The Schr\"odinger functional (SF) is a powerful and widely used tool for the treatment of a variety of problems in renormalization and related areas. Albeit offering many conceptual advantages, one major downside of the SF scheme is the fact that perturbative calculations quickly become cumbersome with the inclusion of higher orders in the gauge coupling and hence the use of an automated perturbation theory framework is desirable. We present the implementation of the SF in numerical stochastic perturbation theory (NSPT) and compare first results for the running coupling at two loops in pure SU(3) Yang-Mills theory with the literature.

Delta M_K and epsilon_K in SUSY at the Next-to-Leading order

1998

We perform a Next-to-Leading order analysis of Delta S=2 processes beyond the Standard Model. Combining the recently computed NLO anomalous dimensions and the B parameters of the most general Delta S=2 effective Hamiltonian, we give an analytic formula for Delta M_K and epsilon_K in terms of the Wilson coefficients at the high energy scale. This expression can be used for any extension of the Standard Model with new heavy particles. Using this result, we consider gluino-mediated contributions to Delta S=2 transitions in general SUSY models and provide an improved analysis of the constraints on off-diagonal mass terms between the first two generations of down-type squarks. Finally, we improv…

Automatic image-based identification and biomass estimation of invertebrates

2020

1. Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. 2. We describe a robot-enabled image-based ident…

Critical comments on EEG sensor space dynamical connectivity analysis

2019

Many different analysis techniques have been developed and applied to EEG recordings that allow one to investigate how different brain areas interact. One particular class of methods, based on the linear parametric representation of multiple interacting time series, is widely used to study causal connectivity in the brain. However, the results obtained by these methods should be interpreted with great care. The goal of this paper is to show, both theoretically and using simulations, that results obtained by applying causal connectivity measures on the sensor (scalp) time series do not allow interpretation in terms of interacting brain sources. This is because (1) the channel locations canno…

Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations

2019

Abstract Satellite remote sensing has been widely used in the last decades for agricultural applications, both for assessing vegetation condition and for subsequent yield prediction. Existing remote sensing-based methods to estimate gross primary productivity (GPP), which is an important variable to indicate crop photosynthetic function and stress, typically rely on empirical or semi-empirical approaches, which tend to over-simplify photosynthetic mechanisms. In this work, we take advantage of all parallel developments in mechanistic photosynthesis modeling and satellite data availability for an advanced monitoring of crop productivity. In particular, we combine process-based modeling with …

Towards realistic artificial benchmark for community detection algorithms evaluation

2013

Many algorithms have been proposed for revealing the community structure in complex networks. Tests under a wide range of realistic conditions must be performed in order to select the most appropriate for a particular application. Artificially generated networks are often used for this purpose. The most realistic generative method to date has been proposed by Lancichinetti, Fortunato and Radicchi (LFR). However, it does not produce networks with some typical features of real-world networks. To overcome this drawback, we investigate two alternative modifications of this algorithm. Experimental results show that in both cases, centralisation and degree correlation values of generated networks…