Détection de mouvements dans des séquences d’images basée sur la dynamique de supraconductivité

Le but de ce travail est d’étudier la faisabilité de la détection de mouvements dans des séquences d’images en utilisant l’équation de continuité et la dynamique de supraconductivité. Notre approche peut être motivée par le fait que l’équation de continuité apparait dans plusieurs techniques qui estiment le flot optique. Un grand nombre de techniques qui utilisent les flots optiques utilisent une contrainte appelée contrainte de l’invariance lumineuse. La dynamique de supraconductivité nous permet de nous affranchir de la contrainte de l’invariance lumineuse. Les expériences se feront avec la base de données de séquences d’images CDNET 2014. Pour obtenir les résultats numériques en terme de score F1, une combinaison sera faite par la suite entre la dynamique de supraconductivité et un méchanisme d’attention qui est un résumé des vérites de terrain.

Étude sur la sécurité dynamique : le cas de Cité-des-Prairies

Travail dirigé présenté à la Faculté des études supérieures en vue de l’obtention du grade de maître ès sciences (M.Sc.) en criminologie option sécurité intérieure

Dynamique holocène de la végétation et des feux d’un paysage contemporain dominé par des espèces de début de succession au sein de la Pessière à mousses de l’Ouest du Québec

Dans le contexte d’études visant à établir des liens entre les paysages forestiers naturels actuels et la façon dont ils se sont transformés au cours de l’Holocène (variabilité naturelle), il est important de définir des stratégies sylvicoles qui répondent aux critères de la mise en place de l’aménagement écosystémique. Au sein du domaine bioclimatique de la pessière à mousses de l’Ouest du Québec, certains paysages forestiers sont aujourd’hui caractérisés par de vastes peuplements de début de succession dominés par le peuplier faux-tremble et le pin gris. Les objectifs de cette étude étaient 1) de reconstituer l’histoire postglaciaire de la végétation et des feux d’un secteur dominé par de tels peuplements, et 2) de préciser leur variabilité naturelle plurimillénaire. À cette fin, les paysages forestiers d’un territoire couvrant une superficie de 4000 km2 dans la région de la plaine du lac Matagami ont d’abord été caractérisés. Dans un deuxième temps, l’histoire de la végétation et des feux a été reconstituée à l’aide de l’analyse pollinique et anthracologique de deux tourbières. Les lieux de prélèvement des sédiments ont été choisis en fonction d’obtenir un enregistrement local et extra-local de l’histoire des forêts jouxtant chacune des tourbières. Les résultats montrent que la majeure partie de l’Holocène (7000 à 1000 ans A.A.) a été caractérisée des feux peu fréquents qui ont permis le maintien de paysages dominés par la pessière noire à sapin baumier. Au cours des 1000 dernières années, des feux plus fréquents et sans doute plus sévères et de plus grandes étendues ont provoqué une diminution de l’abondance du sapin et une augmentation des espèces de début de succession. Les feux du dernier millénaire seraient ainsi à l’origine des actuels peuplements de début de succession qui se maintiendraient selon une dynamique de récurrence.

Étude de la dynamique du ferrofluide appliquée sur une surface générée par plusieurs actionneurs

Le sujet de cette thèse est la caractérisation dynamique d’une surface générée par plusieurs actionneurs d’un miroir ferrofluidique intégré dans un montage d’optique adaptative. Elle conclut un projet de doctorat au sein du groupe Borra s’étant échelonné sur 4 années. Un bref portrait général de l’optique adaptative est d’abord présenté, suivi d’une section sur la théorie du contrôle. Les types de contrôleurs y sont abordés, soit PID et surcharge. L’effet de la viscosité sur la réponse dynamique du système, ainsi que les analyseurs de front d’onde utilisés sont ensuite expliqués. La section résultats est subdivisée en plusieurs sous-sections ordonnées de façon chronologique. Dans un premier temps, il est question des résultats obtenus dans le cadre d’une caractérisation d’un nouveau miroir de 91 actionneurs fabriqué au sein du groupe. Il est ensuite question des résultats obtenus avec diverses techniques telles le PSD et l’imagerie déclenchée. Il y aura toute une section sur les résultats en vitesse, en fonction de la viscosité du liquide, suivie d’une section sur les simulations réalisées avec Simulink afin de bien cibler les limites du système. Les résultats portant sur la technique de surcharge des actionneurs seront ensuite présentés avec des projections futures. La dernière partie de cette thèse portera sur une innovation apportée par un autre membre du groupe. Nous parlerons de la déposition d’une membrane élastomère réfléchissante et de ses effets sur la dynamique du système.

Authentification biométrique par dynamique de frappe pour évaluation à distance utilisant SVM à une classe

La machine à vecteurs de support à une classe est un algorithme non-supervisé qui est capable d’apprendre une fonction de décision à partir de données d’une seule classe pour la détection d’anomalie. Avec les données d’entraînement d’une seule classe, elle peut identifier si une nouvelle donnée est similaire à l’ensemble d’entraînement. Dans ce mémoire, nous nous intéressons à la reconnaissance de forme de dynamique de frappe par la machine à vecteurs de support à une classe, pour l’authentification d’étudiants dans un système d’évaluation sommative à distance à l’Université Laval. Comme chaque étudiant à l’Université Laval possède un identifiant court, unique qu’il utilise pour tout accès sécurisé aux ressources informatiques, nous avons choisi cette chaîne de caractères comme support à la saisie de dynamique de frappe d’utilisateur pour construire notre propre base de données. Après avoir entraîné un modèle pour chaque étudiant avec ses données de dynamique de frappe, on veut pouvoir l’identifier et éventuellement détecter des imposteurs. Trois méthodes pour la classification ont été testées et discutées. Ainsi, nous avons pu constater les faiblesses de chaque méthode dans ce système. L’évaluation des taux de reconnaissance a permis de mettre en évidence leur dépendance au nombre de signatures ainsi qu’au nombre de caractères utilisés pour construire les signatures. Enfin, nous avons montré qu’il existe des corrélations entre le taux de reconnaissance et la dispersion dans les distributions des caractéristiques des signatures de dynamique de frappe.

A methodological approach for the performance optimization of transient seepage models through inverse analysis

The topic of the Ph.D project focuses on the modelling of the soil-water dynamics inside an instrumented embankment section along Secchia River (Cavezzo (MO)) in the period from 2017 to 2018 and the quantification of the performance of the direct and indirect simulations . The commercial code Hydrus2D by Pc-Progress has been chosen to run the direct simulations. Different soil-hydraulic models have been adopted and compared. The parameters of the different hydraulic models are calibrated using a local optimization method based on the Levenberg - Marquardt algorithm implemented in the Hydrus package. The calibration program is carried out using different types of dataset of observation points, different weighting distributions, different combinations of optimized parameters and different initial sets of parameters. The final goal is an in-depth study of the potentialities and limits of the inverse analysis when applied to a complex geotechnical problem as the case study. The second part of the research focuses on the effects of plant roots and soil-vegetation-atmosphere interaction on the spatial and temporal distribution of pore water pressure in soil. The investigated soil belongs to the West Charlestown Bypass embankment, Newcastle, Australia, that showed in the past years shallow instabilities and the use of long stem planting is intended to stabilize the slope. The chosen plant species is the Malaleuca Styphelioides, native of eastern Australia. The research activity included the design and realization of a specific large scale apparatus for laboratory experiments. Local suction measurements at certain intervals of depth and radial distances from the root bulb are recorded within the vegetated soil mass under controlled boundary conditions. The experiments are then reproduced numerically using the commercial code Hydrus 2D. Laboratory data are used to calibrate the RWU parameters and the parameters of the hydraulic model.

Variational and learning models for image and time series inverse problems

Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

A dive into the inverse Galois problem

Il problema inverso di Galois classico consiste nel chiedersi se, dato un gruppo finito G, esista una estensione di Galois del campo dei numeri razionali che abbia come gruppo di Galois il gruppo G. Una volta verificata l'esistenza di una tale estensione poi, si cercano polinomi a coefficienti razionali il cui gruppo di Galois sia G stesso. Noto dall'inizio del diciannovesimo secolo, il problema è tuttora in generale irrisolto, nonostante nel corso degli anni siano stati fatti notevoli progressi. In questa tesi il problema viene affrontato e risolto in alcuni casi particolari: viene mostrata la realizzazione dei gruppi ciclici, dei gruppi abeliani e dei gruppi simmetrici come gruppi di Galois sul campo dei razionali, e vengono dati alcuni esempi di polinomi con tali gruppi di Galois.

Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Association Of Single Nucleotide Polymorphisms In The Gene Encoding Glut1 And Diabetic Nephropathy In Brazilian Patients With Type 1 Diabetes Mellitus.

Mesangial cells subject to high extracellular glucose concentrations, as occur in hyperglycaemic states, are unable to down regulate glucose influx, resulting in intracellular activation of deleterious biochemical pathways. A high expression of GLUT1 participates in the development of diabetic glomerulopathy. Variants in the gene encoding GLUT1 (SLC2A1) have been associated to this diabetic complication. The aim of this study was to test whether polymorphisms in SLC2A1 confer susceptibility to diabetic nephropathy (DN) in Brazilian type 1 diabetes patients. Four polymorphisms (rs3820589, rs1385129, rs841847 and rs841848) were genotyped in a Brazilian cohort comprised of 452 patients. A prospective analysis was performed in 155 patients. Mean duration of follow-up was 5.6±2.4years and the incidence of renal events was 18.0%. The rs3820589 presented an inverse association with the prevalence of incipient DN (OR: 0.36, 95% CI: 0.16 - 0.80, p=0.01) and with progression to renal events (HR: 0.20; 95% CI: 0.03 - 0.70; p=0.009). AGGT and AGAC haplotypes were associated with the prevalence of incipient DN and the AGAC haplotype was also associated with the prevalence of established/advanced DN. In conclusion, rs3820589 in the SLC2A1 gene modulates the risk to DN in Brazilian patients with inadequate type 1 diabetes control.

Association Between Parity, Pre-pregnancy Body Mass Index And Gestational Weight Gain.

To analyze the relationship between parity, pre-pregnancy body mass index (BMI), and gestational weight gain (GWG). This observational controlled study was conducted from November 2013 to April 2014, with postpartum women who started antenatal care up to 14 weeks and had full-term births. Data were collected from medical records and antenatal cards. Descriptive and bivariate analyses were performed. The significance level was 5%. Data were collected from 130 primiparous and 160 multiparous women. At the beginning of prenatal care, 54.62% of the primiparous were eutrophic, while the majority of multiparous were overweight or obese (62.51%). Multiparas are two times more likely to be obese at the beginning of their pregnancies, when compared to primiparas. The average pre-pregnancy weight and final pregnancy weight was significantly higher in multiparous, however, the mean GWG was higher among primiparous. We found an inverse correlation between parity and the total GWG, but initial BMI was significantly higher in multiparas. Nevertheless, monitoring of the GWG through actions that promote a healthier lifestyle is needed, regardless of parity and nutritional status, in order to prevent excessive GWG and postpartum weight retention and consequently inadequate pre-pregnancy nutritional status in future pregnancies.

Correlation Between The Friedman Staging System And The Upper Airway Volume In Patients With Obstructive Sleep Apnea.

This study was designed to evaluate the correlation between computed tomography findings and data from the physical examination and the Friedman Staging System (FSS) in patients with obstructive sleep apnea (OSA). We performed a retrospective evaluation by reviewing the medical records of 33 patients (19 male and 14 female patients) with a mean body mass index of 30.38 kg/m(2) and mean age of 49.35 years. Among these patients, 14 presented with severe OSA, 7 had moderate OSA, 7 had mild OSA, and 5 were healthy. The patients were divided into 2 groups according to the FSS: Group A comprised patients with FSS stage I or II, and group B comprised patients with FSS stage III. By use of the Fisher exact test, a positive relationship between the FSS stage and apnea-hypopnea index (P = .011) and between the FSS stage and body mass index (P = .012) was found. There was no correlation between age (P = .55) and gender (P = .53) with the FSS stage. The analysis of variance test comparing the upper airway volume between the 2 groups showed P = .018. In this sample the FSS and upper airway volume showed an inverse correlation and were useful in analyzing the mechanisms of airway collapse in patients with OSA.

Levantamento e características ecológicas de orchidacea e da mata ciliar do rio dourados, Dourados-MS

The Orchidaceae is one of the largest flowering plants family and with a great importance to conservation. However, no survey on orchid flowers can be found in Mato Grosso do Sul. Thus, the objective of this work was to make a survey of the Orchidaceae species and of its ecology features in a riparian forest in a fragment of Floresta Estacional Semi-Decidual that belongs to the riparian forest of the Dourados River. The inventory was made by using a sweeping method for collection, and in addition to this the vertical and horizontal position of epiphytes were assessed on the hosts. For characterization of microclimate, it was used a thermohygrometer and luximeter. It was identified 17 species of 13 genera. Of the listed genera, the most abundant ones were: Acianthera, Macradenia and Capanemia. It was also noted a vertical and horizontal distribution of the Orchidaceae in relation to inverse gradient of water and light availability. Some species tended to be sensitive to height level categorization, whereas others seemed to occur with similar frequency along the host. In relation to the cardinal orientation, the apparent preferential response for south and east directions was associated to the low sampling effort and lower water availability, which could occur because the north face is opposed to the water body.

Variação na cobertura vegetal nativa em São Paulo: um panorama do conhecimento atual

Studies in several countries have shown the occurrence of forest transition, when forest cover increase overcomes the loss by deforestation. In Brazil, although deforestation is still higher than afforestation, this relationship may be inverse in some regions. Recent assessments suggest the tendency of the state of São Paulo towards forest transition. Aiming to analyze forest transition evidence and facilitate the use of existing information, we review data on native vegetation cover variation in São Paulo from four data sources (Instituto Florestal, SOS MataAtlântica/INPE, IBGE and CATI/IEA). Our results indicate that discrepancies among these assessments may be accounted by differences in methodologies and objectives. We highlight their common grounds and discuss possibilities to harmonize their information.