Orbital stability of standing waves for the nonlinear Schr\"odinger equation with attractive delta potential and double power repulsive nonlinearity

In this paper, a nonlinear Schr\"odinger equation with an attractive (focusing) delta potential and a repulsive (defocusing) double power nonlinearity in one spatial dimension is considered. It is shown, via explicit construction, that both standing wave and equilibrium solutions do exist for certain parameter regimes. In addition, it is proved that both types of wave solutions are orbitally stable under the flow of the equation by minimizing the charge/energy functional.Comment: 30 pages, 5 figure

Energy Distribution in disordered elastic Networks

Disordered networks are found in many natural and artificial materials, from gels or cytoskeletal structures to metallic foams or bones. Here, the energy distribution in this type of networks is modeled, taking into account the orientation of the struts. A correlation between the orientation and the energy per unit volume is found and described as a function of the connectivity in the network and the relative bending stiffness of the struts. If one or both parameters have relatively large values, the struts aligned in the loading direction present the highest values of energy. On the contrary, if these have relatively small values, the highest values of energy can be reached in the struts oriented transversally. This result allows explaining in a simple way remodeling processes in biological materials, for example, the remodeling of trabecular bone and the reorganization in the cytoskeleton. Additionally, the correlation between the orientation, the affinity, and the bending-stretching ratio in the network is discussed

Low-effort place recognition with WiFi fingerprints using deep learning

Using WiFi signals for indoor localization is the main localization modality of the existing personal indoor localization systems operating on mobile devices. WiFi fingerprinting is also used for mobile robots, as WiFi signals are usually available indoors and can provide rough initial position estimate or can be used together with other positioning systems. Currently, the best solutions rely on filtering, manual data analysis, and time-consuming parameter tuning to achieve reliable and accurate localization. In this work, we propose to use deep neural networks to significantly lower the work-force burden of the localization system design, while still achieving satisfactory results. Assuming the state-of-the-art hierarchical approach, we employ the DNN system for building/floor classification. We show that stacked autoencoders allow to efficiently reduce the feature space in order to achieve robust and precise classification. The proposed architecture is verified on the publicly available UJIIndoorLoc dataset and the results are compared with other solutions

Un algoritmo de desrefinamiento en 3D para mallas de tetraedros basado en el esqueleto

En este trabajo, se presenta un nuevo algoritmo de desrefinamiento para mallas de tetraedros no- estructuradas. El algoritmo es el inverso del algoritmo de refinamiento de Plaza y Carey14. Ambos algoritmos funcionan de forma automática. El algoritmo de refinamiento se puede aplicar a cualquier malla inicial de tetraedros. De igual manera el desrefinamiento se puede usar para conseguir una malla más grosera a partir de una secuencia de mallas encajadas obtenidas por medio de la aplicación reiterada del algoritmo de refinamiento. La combinación de ambos algoritmos se puede usar para resolver problemas dependientes del tiempo en dimensión tres, de forma similar a como ya se han usado algoritmos análogos en dimensiones inferiores Ferragut et al 5.Peer Reviewe

Silicon chips inserted into líving cells

Peer Reviewe

RDF/S)XML Linguistic Annotation of Semantic Web Pages

Although with the Semantic Web initiative much research on web pages semantic annotation has already done by AI researchers, linguistic text annotation, including the semantic one, was originally developed in Corpus Linguistics and its results have been somehow neglected by AI. ..