Soluciones de seguridad extremo a extremo con IPsec en una arquitectura I-PEP

Los principales objetivos que se quieren alcanzar con la realizaci on de este proyecto son los siguientes: Estudiar los problemas que padecen las comunicaciones que utilizan el protocolo de transporte TCP en comunicaciones v a sat elite. Familiarizarse con los mecanismo y t ecnicas utilizadas para conseguir mejores rendimientos de los servicios de banda ancha proporcionados v a sat elite. Participar en una nueva propuesta llamada XPLIT para la arquitectura de red satelital que combina el splitting de la conexi on TCP con el intercambio de informaci on cross-layer para mejorar el rendimiento. Estudiar los problemas que surgen al querer aplicar seguridad extremo a extremo, IPsec, sobre una red satelital que utiliza mecanismos de mejora del rendimiento del enlace. Realizar el estudio de una variedad de propuestas para solucionar el problema de la seguridad sobre estas redes. Proponer algunas soluciones al problema haciendo uso de la arquitectura XPLIT analizada

Soluciones de seguridad extremo a extremo con IPsec en una arquitectura I-PEP

Los principales objetivos que se quieren alcanzar con la realizaci on de este proyecto son los siguientes: Estudiar los problemas que padecen las comunicaciones que utilizan el protocolo de transporte TCP en comunicaciones v a sat elite. Familiarizarse con los mecanismo y t ecnicas utilizadas para conseguir mejores rendimientos de los servicios de banda ancha proporcionados v a sat elite. Participar en una nueva propuesta llamada XPLIT para la arquitectura de red satelital que combina el splitting de la conexi on TCP con el intercambio de informaci on cross-layer para mejorar el rendimiento. Estudiar los problemas que surgen al querer aplicar seguridad extremo a extremo, IPsec, sobre una red satelital que utiliza mecanismos de mejora del rendimiento del enlace. Realizar el estudio de una variedad de propuestas para solucionar el problema de la seguridad sobre estas redes. Proponer algunas soluciones al problema haciendo uso de la arquitectura XPLIT analizada

Détection d'un objet immergé dans un fluide

Cette thèse s inscrit dans le domaine des mathématiques appelé optimisation de formes. Plus précisément, nous étudions ici un problème inverse de détection à l aide du calcul de forme et de l analyse asymptotique. L objectif est de localiser un objet immergé dans un fluide visqueux, incompressible et stationnaire. Les questions principales qui ont motivé ce travail sont les suivantes : peut-on détecter un objet immergé dans un fluide à partir d une mesure effectuée à la surface ? peut-on reconstruire numériquement cet objet, i.e. approcher sa position et sa forme, à partir de cette mesure ? peut-on connaître le nombre d objets présents dans le fluide en utilisant cette mesure ?Les résultats obtenus sont décrits dans les cinq chapitres de cette thèse : le premier met en place un cadre mathématique pour démontrer l existence des dérivées de forme d ordre un et deux pour les problèmes de détection d inclusions ; le deuxième analyse le problème de détection à l aide de l optimisation géométrique de forme : un résultat d identifiabilité est montré, le gradient de forme de plusieurs types de fonctionnelles de forme est caractérisé et l instabilité de ce problème inverse est enfin démontrée ; le chapitre 3 utilise nos résultats théoriques pour reconstruire numériquement des objets immergés dans un fluide à l aide d un algorithme de gradient de forme ; le chapitre 4 analyse la localisation de petites inclusions dans un fluide à l aide de l optimisation topologique de forme : le gradient topologique d une fonctionnelle de forme de Kohn-Vogelius est caractérisé ; le dernier chapitre utilise cette dernière expression théorique pour déterminer numériquement le nombre et la localisation de petits obstacles immergés dans un fluide à l aide d un algorithme de gradient topologique.This dissertation takes place in the mathematic field called shape optimization. More precisely, we focus on a detecting inverse problem using shape calculus and asymptotic analysis. The aim is to localize an object immersed in a viscous, incompressible and stationary fluid. This work was motivated by the following main questions: can we localize an obstacle immersed in a fluid from a boundary measurement? can we reconstruct numerically this object, i.e. be close to its localization and its shape, from this measure? can we know how many objects are included in the fluid using this measure?The results are described in the five chapters of the thesis: the first one gives a mathematical framework in order to prove the existence of the shape derivatives oforder one and two in the frame of the detection of inclusions; the second one analyzes the detection problem using geometric shape optimization: an identifiabilityresult is proved, the shape gradient of several shape functionals is characterized and the instability of thisinverse problem is proved; the chapter 3 uses our theoretical results in order to reconstruct numerically some objets immersed in a fluid using a shape gradient algorithm; the fourth chapter analyzes the detection of small inclusions in a fluid using the topological shape optimization : the topological gradient of a Kohn-Vogelius shape functional is characterized; the last chapter uses this theoretical expression in order to determine numerically the number and the location of some small obstacles immersed in a fluid using a topological gradient algorithm.PAU-BU Sciences (644452103) / SudocSudocFranceF

A Newton method for the data completion problem and application to obstacle detection in Electrical Impedance Tomography

The present article is devoted to the study of two well-known inverse problems, that is the data completion problem and the inverse obstacle problem. The general idea is to reconstruct some boundary conditions and/or to identify an obstacle or void of different conductivity which is contained in a domain, from measurements of voltage and currents on (a part of) the boundary of the domain. We focus here on Laplace’s equation. Firstly, we use a penalized Kohn-Vogelius functional in order to numerically solve the data completion problem, which consists in recovering some boundary conditions from partial Cauchy data. The novelty of this part is the use of a Newton scheme in order to solve this problem. Secondly, we propose to build an iterative method for the inverse obstacle problem based on the combination of the previously mentioned data completion subproblem and the so-called trial method. The underlying boundary value problems are efficiently computed by means of boundary integral equations and several numerical simulations show the applicability and feasibility of our new approach

A new method for the data completion problem and application to obstacle detection

The present article is devoted to the study of two well-known inverse problems, that is, the data completion problem and the inverse obstacle problem. The general idea is to reconstruct some boundary conditions and/or to identify an obstacle or void of different conductivity which is contained in a domain, from measurements of voltage and currents on the outer boundary of the domain. We focus here on Laplace's equation. First, we use a penalized Kohn-Vogelius functional in order to numerically solve the data completion problem, which consists in recovering some boundary conditions from partial Cauchy data. The functional to be minimized is quadratic, hence we compute its minimum by solving the linearized equation. Second, we propose to build an iterative method for the inverse obstacle problem based on the combination of the previously mentioned data completion subproblem and the so-called trial method. The underlying boundary value problems are efficiently computed by means of boundary integral equations and several numerical simulations show the applicability and feasibility of our new approach. For the numerical simulations, we focus on star-shaped domains in the two-dimensional case

Identification of Leishmania infantum Epidemiology, Drug Resistance and Pathogenicity Biomarkers with Nanopore Sequencing

The emergence of drug-resistant strains of the parasite Leishmania infantum infecting dogs and humans represents an increasing threat. L. infantum genomes are complex and unstable with extensive structural variations, ranging from aneuploidies to multiple copy number variations (CNVs). These CNVs have recently been validated as biomarkers of Leishmania concerning virulence, tissue tropism, and drug resistance. As a proof-of-concept to develop a novel diagnosis platform (LeishGenApp), four L. infantum samples from humans and dogs were nanopore sequenced. Samples were epidemiologically typed within the Mediterranean L. infantum group, identifying members of the JCP5 and non-JCP5 subgroups, using the conserved region (CR) of the maxicircle kinetoplast. Aneuploidies were frequent and heterogenous between samples, yet only chromosome 31 tetrasomy was common between all the samples. A high frequency of aneuploidies was observed for samples with long passage history (MHOM/TN/80/IPT-1), whereas fewer were detected for samples maintained in vivo (MCRI/ES/2006/CATB033). Twenty-two genes were studied to generate a genetic pharmacoresistance profile against miltefosine, allopurinol, trivalent antimonials, amphotericin, and paromomycin. MHOM/TN/80/IPT-1 and MCRI/ES/2006/CATB033 displayed a genetic profile with potential resistance against miltefosine and allopurinol. Meanwhile, MHOM/ES/2016/CATB101 and LCAN/ES/2020/CATB102 were identified as potentially resistant against paromomycin. All four samples displayed a genetic profile for resistance against trivalent antimonials. Overall, this proof-of-concept revealed the potential of nanopore sequencing and LeishGenApp for the determination of epidemiological, drug resistance, and pathogenicity biomarkers in L. infantum

CosmoHub : Interactive exploration and distribution of astronomical data on Hadoop

We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. CosmoHub, hosted and developed at the Port d'Informacio Científica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ciencies de l'Espai (MICE) numerical simulations. While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. As CosmoHub's datasets are seldomly modified, Hive it is a better fit. Over 60 TiB of catalogued information and 50 × 109 astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. In our current implementation, online exploration of datasets of 109 objects can be done in a timescale of tens of seconds. Users can also download customized subsets of data in standard formats generated in few minutes

CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop

We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. CosmoHub, hosted and developed at the Port d'Informació Científica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ciències de l'Espai (MICE) numerical simulations. While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. As CosmoHub's datasets are seldomly modified, Hive it is a better fit. Over 60 TiB of cataloged information and 50×10 astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. In our current implementation, online exploration of datasets of 10 objects can be done in a timescale of tens of seconds. Users can also download customized subsets of data in standard formats generated in few minutes.CosmoHub has been partially funded through projects of the Spanish national program “Programa Estatal de I + D + i” of the Spanish government. The support of the ERDF fund is gratefully acknowledged

Measuring currents, ice drift, and waves from space: the Sea Surface KInematics Multiscale monitoring (SKIM) concept

We propose a new satellite mission that uses a near-nadir Ka-band Doppler radar to measure surface currents, ice drift and ocean waves at spatial scales of 40?km and more, with snapshots at least every day for latitudes 75 to 82, and every few days otherwise. The use of incidence angles at 6 and 12 degrees allows a measurement of the directional wave spectrum which yields accurate corrections of the wave-induced bias in the current measurements. The instrument principle, algorithm for current velocity and mission performance are presented here. The proposed instrument can reveal features on tropical ocean and marginal ice zone dynamics that are inaccessible to other measurement systems, as well as a global monitoring of the ocean mesoscale that surpasses the capability of today?s nadir altimeters. Measuring ocean wave properties facilitates many applications, from wave-current interactions and air-sea fluxes to the transport and convergence of marine plastic debris and assessment of marine and coastal hazards

CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop

We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. CosmoHub, hosted and developed at the Port d'Informaci\'o Cient\'ifica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ci\`encies de l'Espai (MICE) numerical simulations. While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. As CosmoHub's datasets are seldomly modified, Hive it is a better fit. Over 60 TiB of catalogued information and $50 \times 10^9$ astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. In our current implementation, online exploration of datasets of $10^9$ objects can be done in a timescale of tens of seconds. Users can also download customized subsets of data in standard formats generated in few minutes