Hierarchical Mixtures of Experts and the EM Algorithm

We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM's). Learning is treated as a maximum likelihood problem; in particular, we present an Expectation-Maximization (EM) algorithm for adjusting the parameters of the architecture. We also develop an on-line learning algorithm in which the parameters are updated incrementally. Comparative simulation results are presented in the robot dynamics domain.

A Conservative Front Tracking Algorithm

The discontinuities in the solutions of systems of conservation laws are widely considered as one of the difficulties in numerical simulation. A numerical method is proposed for solving these partial differential equations with discontinuities in the solution. The method is able to track these sharp discontinuities or interfaces while still fully maintain the conservation property. The motion of the front is obtained by solving a Riemann problem based on the state values at its both sides which are reconstructed by using weighted essentially non oscillatory (WENO) scheme. The propagation of the front is coupled with the evaluation of "dynamic" numerical fluxes. Some numerical tests in 1D and preliminary results in 2D are presented.

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

Fast calculation of the CAC convolution algorithm using the multinomial distribution function

The authors focus on one of the methods for connection acceptance control (CAC) in an ATM network: the convolution approach. With the aim of reducing the cost in terms of calculation and storage requirements, they propose the use of the multinomial distribution function. This permits direct computation of the associated probabilities of the instantaneous bandwidth requirements. This in turn makes possible a simple deconvolution process. Moreover, under certain conditions additional improvements may be achieved

A Label space reduction algorithm for P2MP LSPs using asymmetric tunnels

The aim of traffic engineering is to optimise network resource utilization. Although several works on minimizing network resource utilization have been published, few works have focused on LSR label space. This paper proposes an algorithm that uses MPLS label stack features in order to reduce the number of labels used in LSPs forwarding. Some tunnelling methods and their MPLS implementation drawbacks are also discussed. The algorithm described sets up the NHLFE tables in each LSR, creating asymmetric tunnels when possible. Experimental results show that the algorithm achieves a large reduction factor in the label space. The work presented here applies for both types of connections: P2MP and P2P

Speculative parallelization of multipath radiosity algorithm

In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm

Nuevas tecnologías, nuevas formas de negocios: Smartphones y códigos QR en Chile

Hace varios años atrás el uso del celular era un bien que muy pocas personas tenían la oportunidad de adquirirlo. Por un lado esta adquisición era muy cara y además había muy poca oferta en el mercado. El uso de los celulares era estrictamente para llamadas urgentes y muy pocas personas podían tener este bien en sus manos. A medida que iban avanzando los años las personas generaban mas necesidades y las empresas hacían todo lo posible por satisfacer estas necesidades. Por esta misma razón las empresas empezaron a ir más allá que simplemente satisfacer estas necesidades. Por lo que empezaron a no solo crear un simple celular que sirviera para llamadas sino un celular que también incluyera cámara, video, mensajes de texto, mails, bluetooth, música, entre más funciones. Hoy en día un celular que no tenga este tipo de funciones es obsoleto y ahora las personas se vuelven cada vez más dependientes a un teléfono celular. Por eso es importante investigar si es verdaderamente importante y necesario tener toda la vida de las personas en el celular, si estas nuevas tecnologías son relevantes para la sustentabilidad de las empresas y también que beneficios trae la evolución de las nuevas tecnologías. En la actualidad se ha dado que para las personas es fundamental el uso de los smartphones, no solo en la vida personal sino también laboral. Por eso es relevante conocer qué tan importante es el Smartphone para las personas y también cómo se puede aprovechar esta tecnología. Para la sociedad en la que vivimos actualmente, estar en contacto con el mundo es fundamental y también ser parte de el, por lo que la aparición de estos smartphones ha permitido que ese acercamiento sea mas rápido y con mayor facilidad. En los últimos años, ha habido un boom en la oferta y demanda de este tipo de productos, en el cual las empresas han estado peleando por ofrecer tanto nuevos dispositivos y tecnologías, como también nuevos servicios en cuanto a conectividad y aplicaciones de estos.

Educando con QR.

Resumen basado en el de la publicación

QR : Q??digo Rebelde

Se describe una experiencia que consiste en aprender Franc??s a trav??s de c??digos QR (Quick Response). Se especifican las actividades en las que se pueden utilizar estos c??digos y las ventajas de su uso

Cazas del tesoro (Yincanas) con c??digos QR

Resumen basado en el de la publicaci??n

Experiencia de innovaci??n educativa con curso MOOC : los c??digos QR aplicados a la ense??anza

Resumen basado en el de la publicaci??n

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Validation of an automated algorithm for auditory brainstem response testing

This paper discusses the auditory brainstem response (ABR) testing for infants.