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

Surface registration from range image fusion

The registration of full 3-D models is an important task in computer vision. Range finders only reconstruct a partial view of the object. Many authors have proposed several techniques to register 3D surfaces from multiple views in which there are basically two aspects to consider. First, poor registration in which some sort of correspondences are established. Second, accurate registration in order to obtain a better solution. A survey of the most common techniques is presented and includes experimental results of some of them

A review of sensor fusion techniques for underwater vehicle navigation

This work provides a general description of the multi sensor data fusion concept, along with a new classification of currently used sensor fusion techniques for unmanned underwater vehicles (UUV). Unlike previous proposals that focus the classification on the sensors involved in the fusion, we propose a synthetic approach that is focused on the techniques involved in the fusion and their applications in UUV navigation. We believe that our approach is better oriented towards the development of sensor fusion systems, since a sensor fusion architecture should be first of all focused on its goals and then on the fused sensors

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

Fusion 1 : science 11-14.

Proporciona una serie de recursos sobre el funcionamiento integrado del trabajo científico a los alumnos de la etapa 3 de secundaria (key stage 3). Está escrito para cumplir con los requisitos del programa de estudios de 2008, ayuda a desarrollar los conocimientos y habilidades científicos e incluye además actividades e investigaciones prácticas en cada una de las lecciones. Se acompaña del recurso para el profesor.

Fusion 1. Teacher book : science 11-14.

Ayuda a los profesores a planificar las clases de ciencias, contiene referencias al plan de estudios, objetivos y resultados del aprendizaje, habilidades funcionales, notas y sugerencias de deberes para completar las lecciones. Cumple con los requisitos del programa de estudios de 2008 y va destinado a los alumnos de la etapa 3 de secundaria (key stage 3). Se acompaña del libro del alumno.

Fusion 2 : science 11-14.

Proporciona una serie de recursos sobre el funcionamiento integrado del trabajo científico a los alumnos de la etapa 3 de secundaria (key stage 3). Está escrito para cumplir con los requisitos del programa de estudios de 2008, ayuda a desarrollar los conocimientos y habilidades científicos e incluye además actividades e investigaciones prácticas en cada una de las lecciones. Se acompaña del recurso para el profesor.

Fusion 2. Teacher book : science 11-14.

Ayuda a los profesores a planificar las clases de ciencias, contiene referencias al plan de estudios, objetivos y resultados del aprendizaje, habilidades funcionales, notas y sugerencias de deberes para completar las lecciones. Cumple con los requisitos del programa de estudios de 2008 y va destinado a los alumnos de la etapa 3 de secundaria (key stage 3). Se acompaña del libro del alumno.

Fusion 3 : science 11-14.

Proporciona una serie de recursos sobre el funcionamiento integrado del trabajo científico a los alumnos de la etapa 3 de secundaria (key stage 3). Está escrito para cumplir con los requisitos del programa de estudios de 2008, ayuda a desarrollar los conocimientos y habilidades científicos e incluye además actividades e investigaciones prácticas en cada una de las lecciones. Se acompaña del recurso para el profesor.

Fusion 3. Teacher book : science 11-14.

Ayuda a los profesores a planificar las clases de ciencias, contiene referencias al plan de estudios, objetivos y resultados del aprendizaje, habilidades funcionales, notas y sugerencias de deberes para completar las lecciones. Cumple con los requisitos del programa de estudios de 2008 y va destinado a los alumnos de la etapa 3 de secundaria (key stage 3). Se acompaña del libro del alumno.

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.