A 3-3-1 model with low scale seesaw mechanisms

We construct a viable 3-3-1 model with two $SU(3)_L$ scalar triplets, extended fermion and scalar spectrum, based on the $T^{\prime}$ family symmetry and other auxiliary cyclic symmetries, whose spontaneous breaking yields the observed pattern of SM fermion mass spectrum and fermionic mixing parameters. In our model the SM quarks lighter than the top quark, get their masses from a low scale Universal seesaw mechanism, the SM charged lepton masses are produced by a Froggatt-Nielsen mechanism and the small light active neutrino masses are generated from an inverse seesaw mechanism. The model is consistent with the low energy SM fermion flavor data and successfully accommodates the current Higgs diphoton decay rate and predicts charged lepton flavor violating decays within the reach of the forthcoming experiments.Comment: 24 pages, 4 figures. Published versio

La Demanda de Especies Monetarias en Colombia: Estructura y Pronóstico

Las tesorerías de los Bancos Centrales enfrentan el problema de pronosticar las necesidades de especies monetarias requeridas por los agentes económicos para finalizar sus transacciones. Dichos pronósticos son utilizados para hacer sus planes a mediano plazo (2 a 3 años en el caso colombiano) de producción, e inventarios de materia prima y unidades terminadas por denominación. El objetivo de este trabajo es evaluar distintas técnicas de pronóstico que sean lo suficientemente flexibles como para incorporar las innovaciones recientes en los determinantes de la demanda y la estructura denominacional de las especies monetarias, y reconocer las posibles no-linealidades en la relación de aquellos con el uso del efectivo. La estrategia seguida se basa en la utilización de redes neuronales artificiales (ANN) y mínimos cuadrados flexibles (FLS), dos técnicas econométricas bastante robustas frente a cambios estructurales y que permiten incorporar elementos no-lineales en la modelación del efectivo.

Multiple classification of the force and acceleration signals extracted during multiple machine processes: part 1 intelligent classification from an anomaly perspective

This paper is the first in a two-part work, where the investigation into the characteristics of multiple machine processes is made in order to accurately control them via the frequently used machine centre platform. The two machining processes under investigation are grinding and hole making: for grinding anomalies, grinding burn and chatter and for hole making, drilling, increased tool wear and onset of drill tool malfunction, which is also significant to severe scoring and material dragging. Most researchers usually report on one machining process as opposed to multiple which is less consistent with automated flexible systems where more than one machining process must be catered for. For efficient monitoring of automated multiple manufacturing processes, any unwanted anomalies should be identified and dealt with in a prompt and seamless manner. This first part provides two experimental set-ups (same set-up with tool interchange) to obtain signal signatures for both grinding and drilling phenomena (using the same material). Here, an approach based on neural networks and CARTs is used to reliably detect anomalies for both processes using a single acquisition path, opening the door for control implementation

Software to Assist Visually Impaired People During the Craps Game Using Machine Learning on Python Platform

Pattern recognition is a prominent area of research in computer vision, where different methods have been proposed in the last 50 years. This work presents the development of a Python API to identify the result of two six-sided dice used in the game called “Craps” as a no-controlled environment to help visually impaired people. The software is structured in four stages. The first one is capturing images through a device with a digital camera connected to the web via IP address. The second stage corresponds to the captured image processing; it is necessary to establish a standard image size and resize and equalize the digitized image. The third stage seeks to segment the object of study by artificial vision techniques to identify the result of the dice after being thrown. Finally, the fourth stage is to interpret the result and play it through a speaker. The expected possible result is a system that integrates the four stages mentioned above through an intuitive and accessible low-cost Python API, mainly aimed at visually impaired people

On Rogers-Shephard type inequalities for general measures

In this paper we prove a series of Rogers–Shephard type inequalities for convex bodies when dealing with measures on the Euclidean space with either radially decreasing densities or quasi-concave densities attaining their maximum at the origin. Functional versions of classical Rogers–Shephard inequalities are also derived as consequences of our approach