From the real-time forecasting of events to Visual analysis tasks, state-of-the-art machine learning algorithms exhibit unmatched performance. Furthermore, with ongoing traction embedded computing, deployment on mobile devices is receiving increasing attention. There are numerous practical applications where hand-held having methods can be more useful due their compact size and integrated resou...

This work moves from a recent paper by Antoci et al. (2009) [1] where a dynamic model is proposed to describe an innovative method for improving environmental quality based on the exchange of financial activities, promoted by a Public Administration, between firms and tourists in a given region. We extend their analysis in two directions: we first perform a global analysis of the basins of attr...

Keywords: Euler's tallest column Eigenvalue problem under coefficient constraints Nonlocal problem p-Laplacian type operator with a negative exponent Infinite normal derivative a b s t r a c t In 1757, Leonhard Euler started the study of the tallest column, i.e. the shape of a stable column with the symmetry of revolution, such that it attains the maximum height once the total mass is prescribe...

A one-dimensionalmodel of an in vitro experiment, inwhich a specimen of cancellous bone is immersed in water and insonified by an ultrasonic pulse, is considered. Themodification of the poroelastic model of Biot due to Johnson et al. [D.L. Johnson, J. Koplik, R. Dashen, Theory of dynamic permeability and tortuosity in fluid-saturated porous media, J. Fluid Mech. 176 (1987) 379–402] is used for ...

The problem of delay-dependent exponential passivity analysis is investigated for neural networks with time-varying delays. By use of a linear matrix inequality (LMI) approach, a new exponential passivity criterion is proposed via the full use of the information of neuron activation functions and the involved time-varying delays. The obtained results have less conservativeness and less number o...

A new set of methodologies extracts key nonlinearities in the dynamics of financial markets from data that would appear to be completely random with ordinary linear time series methods. The understanding acquired from this analysis forms a basis for modeling conflicting and competing motivations in market decisions. By standardizing the daily changes using the mean and standard deviation, it th...