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

RM qualitative matrix words

Animation that rains down appropriate words relating to qualitative research

El uso de sangre fresca total en cardiopatías congénitas complejas

Objetivos: Describir si el uso de sangre fresca total (SFT) intraoperatoria en pacientes llevados a procedimientos RACHS 3 y 4 en la Fundación Cardioinfantil, disminuye el sangrado postoperatorio y el volumen de transfusión de elementos sanguíneos, en comparación a aquellos en quienes no se usa SFT. Materiales y métodos: Se realizó un estudio de cohorte histórica, tomando una población menor de 1 año expuesta a la sangre fresca total y comparándola con una población de similares características, llevadas a procedimientos de riesgo similar no expuesta. Los análisis se realizaron mediante pruebas estándar para variables continuas y discretas. Un valor de p menor a 0.05 fue aceptado como signficativo. Resultados: 46 pacientes expuestos a SFT y se compararon con 50 pacientes no expuestos. La principal diferencia entre los grupos fue la edad, siendo mayor en el grupo de no expuestos (3.8 años vs 0.9; p<0.001). El volumen de sangrado postoperatorio fue similar, sin embargo los pacientes expuestos a SFT recibieron mayor volumen de transfusiones, sin ser una diferencia estadísticamente significativa (155cc vs 203cc, P=0.9). No hubo diferencia significativa en complicaciones o mortalidad. Conclusiones: En nuestro estudio no se encontró una disminución en el volumen de sangrado postoperatorio en los pacientes menores de 1 año, sometidos a cirugías catalogadas como RACHS 3 y 4, expuestos a SFT, sin embargo se necesitan estudios clínicos controlados que respondan definitivamente a la pregunta.

Prevalencia de enfermedad celiaca en Latinoamérica: revisión sistemática de la literatura y meta-análisis

Introducción: La enfermedad celiaca (EC) es una enfermedad autoinmune (EA) intestinal desencadenada por la ingesta de gluten. Por la falta de información de la presencia de EC en Latinoamérica (LA), nosotros investigamos la prevalencia de la enfermedad en esta región utilizando una revisión sistemática de la literatura y un meta-análisis. Métodos y resultados: Este trabajo fue realizado en dos fases: La primera, fue un estudio de corte transversal de 300 individuos Colombianos. La segunda, fue una revisión sistemática y una meta-regresión siguiendo las guías PRSIMA. Nuestros resultados ponen de manifiesto una falta de anti-transglutaminasa tisular (tTG) e IgA anti-endomisio (EMA) en la población Colombiana. En la revisión sistemática, 72 artículos cumplían con los criterios de selección, la prevalencia estimada de EC en LA fue de 0,46% a 0,64%, mientras que la prevalencia en familiares de primer grado fue de 5,5 a 5,6%, y en los pacientes con diabetes mellitus tipo 1 fue de 4,6% a 8,7% Conclusión: Nuestro estudio muestra que la prevalencia de EC en pacientes sanos de LA es similar a la notificada en la población europea.

Evidencia actual sobre características demográficas en mastitis granulomatosa idiopática

Introducción: La mastitis granulomatosa idiopática es una enfermedad crónica benigna, rara y de etiología desconocida; tiende a confundirse con otras enfermedades debido a síntomas similares. Este estudio pretende identificar y cuantificar las características demográficas, los antecedentes ginecoobstétricos relevantes y las manifestaciones clínicas prediagnósticas de esta enfermedad Metodología: Se realizó una revisión sistemática con análisis agrupado de datos tipo meta análisis. Se utilizó una estrategia de búsqueda en PubMed. Todos los estudios relacionados con la definición, manifestaciones clínicas, diagnóstico, tratamiento y pronóstico de la mastitis granulomatosa idiopática fueron elegibles. Las variables de interés fueron edad, país, antecedente de contracepción hormonal, tiempo de evolución, tiempo desde el último embarazo, diagnóstico inicial, y manifestaciones clínicas previas a la consulta. No hubo restricción en fechas de publicación. Resultados: Fueron incluidas 641 mujeres con diagnóstico de MGI reportadas en 68 publicaciones que cumplieron los criterios de selección. La edad media fue 35.9 años, 14.1% de ellas estaba embarazada o lactando, el antecedente de consumo de anticonceptivos hormonales fue 21% y el tiempo promedio desde el último parto fue de 3.9 años. La afectación ocurre principalmente en mama izquierda y en cuadrante superoexterno. El cáncer de mama y el absceso mamario son diagnósticos diferenciales en la consulta. Discusión: El diagnóstico de MGI es un reto para el ginecólogo desde la consulta inicial. Debido a que sus manifestaciones clínicas no son específicas, su diagnóstico parece apuntar a la necesidad de un proceso de descarte de otras patologías más frecuentes e incluso de peor pronóstico. Palabras clave mastitis granulomatosa idiopática

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.

Evaluation of a feedback equalization algorithm in the CID Wearable Digital Hearing Aid

This paper describes the results of an investigation which examined the efficacy of a feedback equalization algorithm incorporated into the Central Institute for the Deaf Wearable Digital Hearing Aid. The study examined whether the feedback equalization would allow for greater usable gains when subjects listened to soft speech signals, and if so, whether or not this would improve speech intelligibility.