A new Edge Detector Based on Parametric Surface Model: Regression Surface Descriptor

In this paper we present a new methodology for edge detection in digital images. The first originality of the proposed method is to consider image content as a parametric surface. Then, an original parametric local model of this surface representing image content is proposed. The few parameters involved in the proposed model are shown to be very sensitive to discontinuities in surface which correspond to edges in image content. This naturally leads to the design of an efficient edge detector. Moreover, a thorough analysis of the proposed model also allows us to explain how these parameters can be used to obtain edge descriptors such as orientations and curvatures. In practice, the proposed methodology offers two main advantages. First, it has high customization possibilities in order to be adjusted to a wide range of different problems, from coarse to fine scale edge detection. Second, it is very robust to blurring process and additive noise. Numerical results are presented to emphasis these properties and to confirm efficiency of the proposed method through a comparative study with other edge detectors.Comment: 21 pages, 13 figures and 2 table

Sensitivity analysis using Physics-informed neural networks

The paper's goal is to provide a simple unified approach to perform sensitivity analysis using Physics-informed neural networks (PINN). The main idea lies in adding a new term in the loss function that regularizes the solution in a small neighborhood near the nominal value of the parameter of interest. The added term represents the derivative of the loss function with respect to the parameter of interest. The result of this modification is a solution to the problem along with the derivative of the solution with respect to the parameter of interest (the sensitivity). We call the new technique to perform sensitivity analysis within this context SA-PINN. We show the effectiveness of the technique using 3 examples: the first one is a simple 1D advection-diffusion problem to show the methodology, the second is a 2D Poisson's problem with 9 parameters of interest and the last one is a transient two-phase flow in porous media problem.Comment: 22 pages, 11 figure

Apodized pupil Lyot coronagraphs for arbitrary apertures. V. Hybrid Shaped Pupil designs for imaging Earth-like planets with future space observatories

We introduce a new class of solutions for Apodized Pupil Lyot Coronagraphs (APLC) with segmented aperture telescopes to remove broadband diffracted light from a star with a contrast level of $10^{10}$. These new coronagraphs provide a key advance to enabling direct imaging and spectroscopy of Earth twins with future large space missions. Building on shaped pupil (SP) apodization optimizations, our approach enables two-dimensional optimizations of the system to address any aperture features such as central obstruction, support structures or segment gaps. We illustrate the technique with a design that could reach $10^{10}$ contrast level at 34\,mas for a 12\,m segmented telescope over a 10\% bandpass centered at a wavelength $\lambda_0=$500\,nm. These designs can be optimized specifically for the presence of a resolved star, and in our example, for stellar angular size up to 1.1\,mas. This would allow probing the vicinity of Sun-like stars located beyond 4.4\,pc, therefore fully retiring this concern. If the fraction of stars with Earth-like planets is \eta_{\Earth}=0.1, with 18\% throughput, assuming a perfect, stable wavefront and considering photon noise only, 12.5 exo-Earth candidates could be detected around nearby stars with this design and a 12\,m space telescope during a five-year mission with two years dedicated to exo-Earth detection (one total year of exposure time and another year of overheads). Our new hybrid APLC/SP solutions represent the first numerical solution of a coronagraph based on existing mask technologies and compatible with segmented apertures, and that can provide contrast compatible with detecting and studying Earth-like planets around nearby stars. They represent an important step forward towards enabling these science goals with future large space missions.Comment: 9 pages, 6 figures, ApJ accepted on 01/04/201

Advanced signal processing methods in dynamic contrast enhanced magnetic resonance imaging

Tato dizertační práce představuje metodu zobrazování perfúze magnetickou rezonancí, jež je výkonným nástrojem v diagnostice, především v onkologii. Po ukončení sběru časové sekvence T1-váhovaných obrazů zaznamenávajících distribuci kontrastní látky v těle začíná fáze zpracování dat, která je předmětem této dizertace. Je zde představen teoretický základ fyziologických modelů a modelů akvizice pomocí magnetické rezonance a celý řetězec potřebný k vytvoření obrazů odhadu parametrů perfúze a mikrocirkulace v tkáni. Tato dizertační práce je souborem uveřejněných prací autora přispívajícím k rozvoji metodologie perfúzního zobrazování a zmíněného potřebného teoretického rozboru.This dissertation describes quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), which is a powerful tool in diagnostics, mainly in oncology. After a time series of T1-weighted images recording contrast-agent distribution in the body has been acquired, data processing phase follows. It is presented step by step in this dissertation. The theoretical background in physiological and MRI-acquisition modeling is described together with the estimation process leading to parametric maps describing perfusion and microcirculation properties of the investigated tissue on a voxel-by-voxel basis. The dissertation is divided into this theoretical analysis and a set of publications representing particular contributions of the author to DCE-MRI.

Application of geotechnical monitoring in tunnels with neural networks and finite elements methods

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Σχεδιασμός και Κατασκευή Υπόγειων Έργων

Design, Development, and Modeling of a Compact, Field-Grade Civil Infrastructure Crack Detector Device

Currently the nation's aging bridge infrastructure is approaching and in some cases exceeding its initial design life averaging more than forty years. Under these conditions steel bridges are susceptible to fatigue cracks at stress ranges below their material yield strength. In order to evaluate the remaining service life of these structures under their current operating conditions, it is important to accurately locate and identify active cracks within the material. Early detection of cracks and defects within a structure can provide inspectors and bridge maintenance personnel with viable information that can be used in the design and selection of an appropriate retrofit or repair technique that can be used to extend the service life of the bridge structure. Bridge inspections are typically conducted every two years primarily using visual inspection techniques. The active crack sensing tool designed and analyzed in this study is based on the robust and high sensing capabilities of piezoceramic materials. This dissertation presents the analytical, computational, and experimental results of a novel approach to identifying and characterizing cracks in steel bridge structural components using a piezoceramic sensor. Using the newly designed Piezoelectric Active Crack Tip Sensor (PACTS) tool, it was possible to detect an active crack with an opening displacement of 0.056 mm [0.0022 in] could be sensed under dynamic loading conditions. By using a crack opening linear trend (COLT) analysis, the crack tip position could be located within 3 mm [1/8 in] without the use of correction or modification factors. The results of the research provide a foundation in establishing an inspection tool capable of identifying damage detection within an in-service structure. The identification of an active crack and the ability to locate the crack tip of a material provides bridge inspectors and maintenance personnel with valuable information related to the current bridge condition that could be used for maintenance, repair, or replacement of bridges structures in an effort to ensure the safe passage of people and goods across the nation