Search results for "Modeling"

A Spline Collocation Scheme for the Spherical Shallow Water Equations

1999

Effective strategies for targeted attacks to the network of Cosa Nostra affiliates

2022

AbstractNetwork dismantling has recently gained interest in the fields of intelligence agencies, anti-corruption analysts and criminal investigators due to its efficiency in disrupting the activity of malicious agents. Here, we apply this approach to detect effective strategies for targeted attacks to Cosa Nostra by analysing the collaboration network of affiliates that participate to the same crimes. We preliminarily detect statistically significant homophily patterns induced by being member of the same mafia syndicate. We also find that links between members belonging to different mafia syndicates play a crucial role in connecting the network into a unique component, confirming the releva…

On optimal estimates for the solutions of linear difference equations on the circle

1976

A linear difference equation arising in the proof of Moser's twist mapping theorem is solved and optimal estimates for the solution are established.

Navigationsformel zu A. Busemanns Variationsproblem der Raumfahrt

1970

Die Indikatrix des Variationsproblems wird auser durch die Storungsdifferentialgleichung fur die grose Halbachse und die Exzentrizitat durch einen Zusammenhang zwischen der Richtung des Impulsausstoses und der exzentrischen Anomalie gegeben. Die Hamilton-Gleichungen einer Extremalen reduzieren sich dann auf eine Navigationsgleichung. Die restlichen Storungsgleichungen fur die Perihellange und die mittlere Lange der Epoche geben schlieslich den sparsamsten zeitlichen Ablauf des Raketenausstoses.

Shooting methods for 1D steady-state free boundary problems

1993

AbstractIn this note, we present two numerical methods based on shooting methods to solve steady-state diffusion-absorption models.

Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

2021

To date, computational approaches have been recognized as a key component in drug design and discovery workflows. Developed to help researchers save time and reduce costs, several computational tools have been developed and implemented in the last twenty years. At present, they are routinely used to identify a therapeutic target, understand ligand–protein and protein–protein interactions, and identify orthosteric and allosteric binding sites, but their primary use remains the identification of hits through ligand-based and structure-based virtual screening and the optimization of lead compounds, followed by the estimation of the binding free energy. The repurposing of an old drug for the tr…

Comparison of implementations of the lattice-Boltzmann method

2008

AbstractSimplicity of coding is usually an appealing feature of the lattice-Boltzmann method (LBM). Conventional implementations of LBM are often based on the two-lattice or the two-step algorithm, which however suffer from high memory consumption and poor computational performance, respectively. The aim of this work was to identify implementations of LBM that would achieve high computational performance with low memory consumption. Effects of memory addressing schemes were investigated in particular. Data layouts for velocity distribution values were also considered, and they were found to be related to computational performance. A novel bundle data layout was therefore introduced. Address…

Stochastic analysis of dynamical systems with delayed control forces

2006

Abstract Reduction of structural vibration in actively controlled dynamical system is usually performed by means of convenient control forces dependent of the dynamic response. In this paper the existent studies will be extended to dynamical systems subjected to non-normal delta-correlated random process with delayed control forces. Taylor series expansion of the control forces has been introduced and the statistics of the dynamical response have been obtained by means of the extended Ito differential rule. Numerical application provided shows the capabilities of the proposed method to analyze stochastic dynamic systems with delayed actions under delta-correlated process contrasting statist…

A 3D multi-physics boundary element computational framework for polycrystalline materials micro-mechanics

2021

A recently developed novel three-dimensional (3D) computational framework for the analysis of polycrystalline materials at the grain scale is described in this lecture. The framework is based on the employment of: i) 3D Laguerre-Voronoi tessellations for the representation of the micro-morphology of polycrystalline materials; ii) boundary integral equations for the representation of the mechanics of the individual grains; iii) suitable cohesive traction-separation laws for the representation of the multi-physics behavior of the interfaces (either inter-granular or trans-granular) within the aggregate, which are the seat of damage initiation and evolution processes, up to complete decohesion…

Sequence Learning in a Single Trial: A Spiking Neurons Model Based on Hippocampal Circuitry.

2020

ABSTRACTIn contrast with our everyday experience using brain circuits, it can take a prohibitively long time to train a computational system to produce the correct sequence of outputs in the presence of a series of inputs. This suggests that something important is missing in the way in which models are trying to reproduce basic cognitive functions. In this work, we introduce a new neuronal network architecture that is able to learn, in a single trial, an arbitrary long sequence of any known objects. The key point of the model is the explicit use of mechanisms and circuitry observed in the hippocampus, which allow the model to reach a level of efficiency and accuracy that, to the best of our…