(1) time Parallel Agorithm for Finding 2D Convex Hull on a Reconfigurable Mesh Computer Architecture

In this paper we propose a parallel algorithm in image processing in (1) time, intended for a parallel machine '' Reconfigurable Mesh Computer (RMC), of size n x n Elementary Processors (PE). The algorithm consists in determining the convex envelope of a two-level 2D image with a complexity in (1) time. The approach used is purely geometric. It is based solely on the projection of the coordinates of PEs retained in specific quadrants and on the application of the algorithm that determines the Min / Max in (1) time. This has reduced the complexity of the algorithm for determining the convex hull at (1) time

Enabling wireless in-band full-duplex

This paper presents a baseband model and an enhanced implementation of the wireless full duplex analog method introduced by [1].Unlike usual methods based on hardware and software self- interference cancelation, the proposed design relies on FSK modulation. The principle is when the transmitter of a local end is sending data by modulating the carrier with the appropriate frequency deviation, its own receiver is checking if the remote transmitter is using the opposite deviation. Instead of architectures often used by both non-coherent and coherent receivers that require one filter (matched filter for coherent detection) for each frequency deviation, our design uses one mixer and one single integrator-decimator filter. We test our design using Universal Software Radio Peripheral as radio frequency front end and computer that implements the signal processing methods under free and open source software. We validate our solution experimentally and we show that in-band full duplex is feasible and synthesizable for wireless communications

Θ(1) Time Algorithm for Master Selection in Ad-hoc Wireless Networks

This paper details a hardware implementation of a distributed Θ(1) time algorithm allows to select dynamically the master device in ad-hoc or cluster-based networks in a constant time regardless the number of devices in the same cluster. The algorithm allows each device to automatically detect its own status; master or slave; based on identifier without adding extra overheads or exchanging packets that slow down the network. We propose a baseband design that implements algorithm functions and we detail the hardware implementation using Matlab/Simulink and Ettus B210 USRP. Tests held in laboratory prove that algorithm works as expected

Design and analysis of a new multi-level inverter topology with a reduced number of switches and controlled by PDPWM technique

With their many advantages, including low power dissipation in power switches, low harmonic content, and reduced electromagnetic interference (EMI) from the inverter, multilevel converter (MLI) topologies are becoming more and more in demand in high and medium power applications. This paper introduces a novel multi-level symmetric inverter topology with adopted control. The objectives of this article are to architecturally define the positions of the various switches, to choose the right switches and to propose an inverter control strategy that will eliminate harmonics while producing the ideal output voltage/current. By using fewer switching elements, fewer voltage sources, and switches with a total harmonic content (THD) which reduces losses and a drop in minimum voltage (Vstrssj), the proposed topology is more efficient than conventional inverters with the same number of levels. The new topology will be demonstrated using a seven-level single-phase inverter. For various modulation indices, MATLAB-SIMULINK is used to study and validate the topology

Single solar cell ideality factor determination using a fixed point method

The modeling and extraction of solar cell parameters are the crucial steps for simulating and optimizing the photovoltaic systems to meet specific properties. These parameters are directly related to the current-voltage characteristic of the solar cell under illumination, the latter is generally represented, by an equivalent electrical circuit whose parameters (the shunt resistance, the saturation current, the series resistance and the ideality factor of the diode) have been the subject of several researches. This paper describes an iterative algorithm based on fixed point method to calculate the ideality factor of a photovoltaic cell. The procedure uses the electrical and mathematical equations governing the solar cell behavior. The obtained results were compared to the previous works to show its effeteness

Parallel Algorithm for Brain Tissues Segmentation in T1-Weighted MR Images on 3D Reconfigurable Mesh Computer

In this paper, we propose a parallel algorithm for brain tissues segmentation from T1-weighted Magnetic Resonance Images (MRI) on Massively Parallel architecture named reconfigurable mesh computer (MCR), this brain tissues are already extracted using our method named Threshold Morphologic Brain Extraction method (TMBE)[1]. The use of this massively parallel architecture is introduced in order to improve the complexities of the corresponding algorithms. The image of size (M x N x K) to be processed must be stored on the RMC of the same size, one Voxel per Processing Element (PE). The proposed method consists in the brain tissues segmentation using parallel version of the modified fuzzy c-means MFCM [2], named PMFCM. This algorithm is directly applied on the extracted volume. The corresponding parallel program of the proposed algorithm is validated on a 3D Reconfigurable Mesh emulator [3]

Vers une accélération performante des applications de traitement d’images sur architectures parallèles

Les systèmes parallèles et distribués sont devenus, depuis quelques années, des incontournables issues pour le domaine du calcul de haute performance. Selon les problèmes et les contextes considérés, plusieurs architectures parallèles et techniques algorithmiques de distribution de données et de traitements sont apparus. Dans ce papier nous nous proposons, à travers une revue de littérature et un retour d’expérience, quelques aspects fondamentaux liés aux différents enjeux mis au cours de cette transformation de paradigme séquentiel-parallèle ainsi que les différentes contraintes auxquels la communauté technique et scientifique doit vaincre. L’accent est mis sur les applications et les algorithmes de traitement d’images accélérés via des architectures parallèles de type GPU. Une validation concrète, à travers une étude comparative de performances de trois algorithmes de classification floue appliqués à la segmentation d’images médicales, est présenté

Data science for modeling disease interactions: a baseline algorithm

Multimorbidity is one of the major problems in recent health care systems, the more conditions the patients suffer from, the worst psychological pressures are put upon these patients. We formulate Multimorbidity detection as a hypergraph learning problem. Then we propose an implementation of a multimorbidity pattern detection using Multimorbidity coefficient score. This pairwise based algorithm can be considered as a baseline to which other data-driven and machine learning techniques for multimorbidity pattern detection can be evaluated. We illustrate this algorithm by building a co-occurrence model for comorbid diseases over psycho-social profiles present in a real dataset. Based on the comorbidity network of diseases, we conducted mesoscopic analysis using centrality analysis of network disease/nodes and determined potential components of the network using community detection algorithms. The patterns detected in this work by the used algorithms reveal first, that the proposed algorithm can be used as a baseline to other approaches. Second, that aging does not influence the risk of developing Multimorbidity diseases just in quantity, but also in complexity