Search results for " Computer"
showing 10 items of 6910 documents
Recent progress in electrical impedance tomography
2003
We consider the inverse problem of finding cavities within some body from electrostatic measurements on the boundary. By a cavity we understand any object with a different electrical conductivity from the background material of the body. We survey two algorithms for solving this inverse problem, namely the factorization method and a MUSIC-type algorithm. In particular, we present a number of numerical results to highlight the potential and the limitations of these two methods.
A regularized Newton method for locating thin tubular conductivity inhomogeneities
2011
We consider the inverse problem of determining the position and shape of a thin tubular object, such as for instance a wire, a thin channel or a curve-like crack, embedded in some three-dimensional homogeneous body from a single measurement of electrostatic currents and potentials on the boundary of the body. Using an asymptotic model describing perturbations of electrostatic potentials caused by such thin objects, we reformulate the inverse problem as a nonlinear operator equation. We establish Frechet differentiability of the corresponding operator, compute its Frechet derivative and set up a regularized Newton scheme to solve the inverse problem numerically. We discuss our implementation…
Jacobian of solutions to the conductivity equation in limited view
2022
Abstract The aim of hybrid inverse problems such as Acousto-Electric Tomography or Current Density Imaging is the reconstruction of the electrical conductivity in a domain that can only be accessed from its exterior. In the inversion procedure, the solutions to the conductivity equation play a central role. In particular, it is important that the Jacobian of the solutions is non-vanishing. In the present paper we address a two-dimensional limited view setting, where only a part of the boundary of the domain can be controlled by a non-zero Dirichlet condition, while on the remaining boundary there is a zero Dirichlet condition. For this setting, we propose sufficient conditions on the bounda…
Involvement of acyl coenzyme A oxidase isozymes in biotransformation of methyl ricinoleate into gamma-decalactone by Yarrowia lipolytica.
2000
ABSTRACT We reported previously on the function of acyl coenzyme A (acyl-CoA) oxidase isozymes in the yeast Yarrowia lipolytica by investigating strains disrupted in one or several acyl-CoA oxidase-encoding genes ( POX1 through POX5 ) (H. Wang et al., J. Bacteriol. 181:5140–5148, 1999). Here, these mutants were studied for lactone production. Monodisrupted strains produced similar levels of lactone as the wild-type strain (50 mg/liter) except for Δ pox3 , which produced 220 mg of γ-decalactone per liter after 24 h. The Δ pox2 Δpox3 double-disrupted strain, although slightly affected in growth, produced about 150 mg of lactone per liter, indicating that Aox2p was not essential for the biotra…
A Hardware and Secure Pseudorandom Generator for Constrained Devices
2018
Hardware security for an Internet of Things or cyber physical system drives the need for ubiquitous cryptography to different sensing infrastructures in these fields. In particular, generating strong cryptographic keys on such resource-constrained device depends on a lightweight and cryptographically secure random number generator. In this research work, we have introduced a new hardware chaos-based pseudorandom number generator, which is mainly based on the deletion of an Hamilton cycle within the $N$ -cube (or on the vectorial negation), plus one single permutation. We have rigorously proven the chaotic behavior and cryptographically secure property of the whole proposal: the mid-term eff…
Langage et Apprentissage en Interaction pour des Assistants Numériques Autonomes - Une Approche Développementale
2021
The rapid development of digital assistants (DA) opens the way to new modes of interaction. Some DA allows users to personalise the way they respond to queries, in particular by teaching them new procedures. This work proposes to use machine learning methods to enrich the linguistic and procedural generalisation capabilities of these systems. The challenge is to reconcile rapid learning skills, necessary for a smooth user experience, with a sufficiently large generalisation capacity. Though this is a natural human ability, it remains out-of-reach for artificial systems and this leads us to approach these issues from the perspective of developmental Artificial Intelligence. This work is thus…
Artificial intelligence for image-guided prostate brachytherapy procedures
2020
Radiotherapy procedures aim at exposing cancer cells to ionizing radiation. Permanently implanting radioactive sources near to the cancer cells is a typical technique to cure early-stage prostate cancer. It involves image acquisition of the patient, delineating the target volumes and organs at risk on different medical images, treatment planning, image-guided radioactive seed delivery, and post-implant evaluation. Artificial intelligence-based medical image analysis can benefit radiotherapy procedures. It can help to facilitate and improve the efficiency of the procedures by automatically segmenting target organs and extrapolating clinically relevant information. However, manual delineation…
Computer-aided-diagnosis for ocular abnormalities from a single color fundus photography with deep learning
2023
Any damage to the retina can lead to severe consequences like blindness. This visual impairment is preventable by early detection of ocular abnormalities. Computer-aided diagnosis (CAD) for ocular abnormalities is built by analyzing retinal imaging modalities, for instance, Color Fundus Photography (CFP). The main objectives of this thesis are to build two CAD models, one to detect the microaneurysms (MAs), the first visible symptom of diabetic retinopathy, and the other for multi-label detection of 28 ocular abnormalities consisting of frequent and rare abnormalities from a single CFP by using deep learning-based approaches. Two methods were proposed for MAs detection: ensemble-based and c…
Hop: Histogram of patterns for human action representation
2017
This paper presents a novel method for representing actions in terms of multinomial distributions of frequent sequential patterns of different length. Frequent sequential patterns are series of data descriptors that occur many times in the data. This paper proposes to learn a codebook of frequent sequential patterns by means of an apriori-like algorithm, and to represent an action with a Bag-of-Frequent-Sequential-Patterns approach. Preliminary experiments of the proposed method have been conducted for action classification on skeletal data. The method achieves state-of-the-art accuracy value in cross-subject validation.
A comparison of two different formulations for Arc Routing Problems on Mixed graphs
2006
[EN] Arc routing problems on mixed graphs have been modelled in the literature either using just one variable per edge or associating to each edge two variables, each one representing its traversal in the corresponding direction. In this paper, and using the mixed general routing problem as an example, we compare theoretical and computationally both formulations as well as the lower bounds obtained from them using Linear Programming based methods. Extensive computational experiments, including some big and newly generated random instances, are presented.