Radioactivity Distribution In Surface And Core Sediment Of The Central Part Of The Algerian Coast: An Estimation Of The Recent Sedimentation Rate

Sediment core samples and marine surface sediments of identical composition, mostly muddy, were collected using a Van Veen type grab and a box corer on board the M.S. Benyahia research vessel (ISMAL), along the Algerian littoral, between Algiers (36Ζ49.9 N/ 03Ζ 02.3 E) and Cherchell (36Ζ 39.4 N/ 02Ζ 12.4 E), during a sampling cruise in September 1997. The samples were analysed to determine the activity concentration of natural radionuclides (uranium and thorium series and 40 K as well) and artificial radionuclides ( 137 Cs and Pu isotopes), using a direct gamma spectrometry for gamma emitters and radiochemical separations and alpha spectrometry for alpha emitters. The horizontal and vertical distribution of the examined radionuclides were studied in the surface and core samples and an effort to estimate the sedimentation rate was attempted.The measured values range was: 17 - 26 Bq/Kg dry for uranium series radioisotopes, 18 – 32 Bq/Kg dry for thorium series radioisotopes, 311 - 690 Bq/Kg dry for 40 K, 0.4 - 11 Bq/Kg dry, for 137 Cs and 0.4 – 1.0 Bq/Kg dry for 239 + 240 Pu

Novel Dynamic Partial Reconfiguration Implementation of K-Means Clustering on FPGAs: Comparative Results with GPPs and GPUs

K-means clustering has been widely used in processing large datasets in many fields of studies. Advancement in many data collection techniques has been generating enormous amounts of data, leaving scientists with the challenging task of processing them. Using General Purpose Processors (GPPs) to process large datasets may take a long time; therefore many acceleration methods have been proposed in the literature to speed up the processing of such large datasets. In this work, a parameterized implementation of the K-means clustering algorithm in Field Programmable Gate Array (FPGA) is presented and compared with previous FPGA implementation as well as recent implementations on Graphics Processing Units (GPUs) and GPPs. The proposed FPGA has higher performance in terms of speedup over previous GPP and GPU implementations (two orders and one order of magnitude, resp.). In addition, the FPGA implementation is more energy efficient than GPP and GPU (615x and 31x, resp.). Furthermore, three novel implementations of the K-means clustering based on dynamic partial reconfiguration (DPR) are presented offering high degree of flexibility to dynamically reconfigure the FPGA. The DPR implementations achieved speedups in reconfiguration time between 4x to 15x

Plutonium Isotopes Concentration in Seawater along the Algerian Coast

The International Atomic Energy Agency has organised in the framework of the regional project RAF/7/004, in collaboration with “Commissariat à l'Energie Atomique” (COMENA) and “Institut des Sciences de la Mer et de l'Aménagement du Littoral” (ISMAL), during August 2001, a scientific campaign along the Algerian coast, on board of the research vessel M.S. Benyahia of ISMAL is. Three stations, at the centre, east and west, were selected to collect five seawater samples for each water column reaching a maximum depth of 2000 m, using a stainless-steel water sampler of a volume of 250 litres. After recording the marine environment parameters (temperature and conductivity), seawater samples were conditioned and preconcentrated to precipitate plutonium isotopes using MnCl2 in the form of MnO2 in order to proceed to plutonium extraction by radiochemical separation and prepare the source by coprecipitation using neodymium fluoride (NdF3) by vacuum filtration and an evaluation of the activity by alpha spectrometry. Concentration results in units of μBq/l of plutonium isotopes were obtained in the range of 6.7±1.00 to 25.5±3.70 for P239+240u and 0.21±0.04 to 0.77±0.15 for P238u. Distribution of Pu through the plot of its profile was studied and the concentration was estimated. The obtained results were compared toC137s and those found by other authors in the same Mediterranean area

CARI'96 : actes du 3ème colloque africain sur la recherche en informatique = CARI'96 : proceedings of the 3rd African conference on research in computer science

Cet article présente quelques solutions ayant pour but d'améliorer la testabilité des circuits combinatoires testés de manière pseudo-aléatoire. S'inscrivant dans l'approche Force-Observe, les solutions préconisées consistent en la modification des circuits par l'insertion de deux types de points de test : les points d'observation et les points de contrôle. (Résumé d'auteur

Reconfiguration-based implementation of SVM classifier on FPGA for classifying microarray data.

Classifying Microarray data, which are of high dimensional nature, requires high computational power. Support Vector Machines-based classifier (SVM) is among the most common and successful classifiers used in the analysis of Microarray data but also requires high computational power due to its complex mathematical architecture. Implementing SVM on hardware exploits the parallelism available within the algorithm kernels to accelerate the classification of Microarray data. In this work, a flexible, dynamically and partially reconfigurable implementation of the SVM classifier on Field Programmable Gate Array (FPGA) is presented. The SVM architecture achieved up to 85× speed-up over equivalent general purpose processor (GPP) showing the capability of FPGAs in enhancing the performance of SVM-based analysis of Microarray data as well as future bioinformatics applications