This dissertation is concerned with the problem of estimating travel time per links in urban context using sparsely sampled GPS data. One of the challenges in this thesis is use the sparsely sampled data. A part of this research work, i developed a digital map with its new geographic information system (GIS), dealing with map-matching problem, where we come out with an enhancement tecnique, and also the shortest path problem.The thesis research work was conduct within the project PUMAS, which is an avantage for our research regarding the collection process of our data from the real world field and also in making our tests. The project PUMAS (Plate-forme Urbaine de Mobilité Avancée et Soutenable / Urban Platform for Sustainable and Advanced Mobility) is a preindustrial project that has the objective to inform about the traffic situation and also to develop an implement a platform for sustainable mobility in order to evaluate it in the region, specifically Rouen, France. The result is a framework for any traffic controller or manager and also estimation researcher to access vast stores of data about the traffic estimation, forecasting and status.

The continuous advancement in wireless communications technology demands new approaches to improving the capacity of existing radio links. The high data throughput required can be achieved by the complete utilization of space, time and polarization diversities inherent in any propagation environment. Among the different propagation scenarios, the indoor channels represent a particularly challenging problem given the number and complexity of interactions between the transmitted signal and the environment. This dissertation explores the interrelation between propagation physics and space-time-polarization diversity based on a novel high resolution channel sounding and reconstruction technique. First, a method to reconstruct the indoor complex channel response based on a limited set of samples and the elimination of the interference using deconvolution techniques is presented. Then, the results for the joint angle-of-arrival, delay characterization and depolarization of electromagnetic waves are presented. Finally, a novel approach to using depolarized multipath signals to boost the receiver signal-to-noise performance is presented. The current study shows that full utilization of the diversities of channel novel wireless systems can be proposed with significant improvement in capacity.

Understanding human behaviour is key to understanding the spread of epidemics, habit dispersion, and the efficacy of health interventions. Investigation into the patterns of and drivers for human behaviour has often been facilitated by paper tools such as surveys, journals, and diaries. These tools have drawbacks in that they can be forgotten, go unfilled, and depend on often unreliable human memories. Researcher-driven data collection mechanisms, such as interviews and direct observation, alleviate some of these problems while introducing others, such as bias and observer effects. In response to this, technological means such as special-purpose data collection hardware, wireless sensor networks, and apps for smart devices have been built to collect behavioural data. These technologies further reduce the problems experienced by more traditional behavioural research tools, but often experience problems of reliability, generality, extensibility, and ease of configuration. This document details the construction of a smartphone-based app designed to collect data on human behaviour such that the difficulties of traditional tools are alleviated while still addressing the problems faced by modern supplemental technology. I describe the app's main data collection engine and its construction, architecture, reliability, generality, and extensibility, as well as the programming language developed to configure it and its feature set. To demonstrate the utility of the tool and its configuration language, I describe how they have been used to collect data in the field. Specifically, eleven case studies are presented in which the tool's architecture, flexibility, generality, extensibility, modularity, and ease of configuration have been exploited to facilitate a variety of behavioural monitoring endeavours. I further explain how the engine performs data collection, the major abstractions it employs, how its design and the development techniques used ensure ongoing reliability, and how the engine and its configuration language could be extended in the future to facilitate a greater range of experiments that require behavioural data to be collected. Finally, features and modules of the engine's encompassing system, iEpi, are presented that have not otherwise been documented to give the reader an understanding of where the work fits into the larger data collection and processing endeavour that spawned it.

隨著地籍管理工作在廣度深度上的增加，使得地籍、土地利用等歷史資料的查詢與檢索日益頻繁，但現階段地籍管理系統之建置方法對於歷史資料查詢之效率較差。本文在探討含時間維度資料庫之建置方法，並利用異動時間與異動註記等欄位及異動紀錄表之建立，令目前地籍管理系統可達到以時間維度，或指定地號，進行地籍資料查詢與檢索。 / The more cadastral management is developed, the more historic data query of cadastre and land use are important. The primary purpose of this study is concentrated on the recoveries of parcel linage and areas on any time profile. The targets of this research are placed on design of spatio-temporal data model, and the analysis of efficiency of data recovery and query.

When statistical assumptions do not hold and coherent structures are present in spatially extended systems such as fluid flows, flame fronts and field theories, a dynamical description of turbulent phenomena becomes necessary. In the dynamical systems approach, theory of turbulence for a given system, with given boundary conditions, is given by (a) the geometry of its infinite-dimensional state space and (b) the associated measure, that is, the likelihood that asymptotic dynamics visits a given state space region. In this thesis this vision is pursued in the context of Kuramoto-Sivashinsky system, one of the simplest physically interesting spatially extended nonlinear systems. With periodic boundary conditions, continuous translational symmetry endows state space with additional structure that often dictates the type of observed solutions. At the same time, the notion of recurrence becomes relative: asymptotic dynamics visits the neighborhood of any equivalent, translated point, infinitely often. Identification of points related by the symmetry group action, termed symmetry reduction, although conceptually simple as the group action is linear, is hard to implement in practice, yet it leads to dramatic simplification of dynamics. Here we propose a scheme, based on the method of moving frames of Cartan, to efficiently project solutions of high-dimensional truncations of partial differential equations computed in the original space to a reduced state space. The procedure simplifies the visualization of high-dimensional flows and provides new insight into the role the unstable manifolds of equilibria and traveling waves play in organizing Kuramoto-Sivashinsky flow. This in turn elucidates the mechanism that creates unstable modulated traveling waves (periodic orbits in reduced space) that provide a skeleton of the dynamics. The compact description of dynamics thus achieved sets the stage for reduction of the dynamics to mappings between a set of Poincare sections.

L’évolution des mises en liens en réponse aux changements globaux et à la globalisation contemporaine précipite le risque d’émergence infectieuse. Dans cette recherche, nous dressons une géographie des vulnérabilités territoriales face à l’émergence des risques zoonotiques. Notre cas d’étude est celui des dynamiques d’invasion d’un hôte commensal, le rat noir (Rattus rattus), dans les marges orientales du Sénégal, périphérie rurale ouest-africaine en mutation. Nous défendons l’idée que les sociétés façonnent des systèmes territoriaux inégalement vulnérables à la diffusion spatiale de l’hôte.Nous montrons que les espaces du Sénégal Oriental et leurs mises en liens se transforment sous l’action des multiples acteurs territoriaux. Les dynamiques d’invasion du rat noir reflètent ces évolutions. Pourtant, les facteurs spatiaux de diffusion des lieux, des foyers, et des chemins d’invasion sont inopérants pour expliquer les dynamiques spatio-temporelles de l’hôte. En outre, la distribution spatiale du rongeur apparaît en contradiction avec les modèles classiques de diffusion fondés sur la hiérarchie ou la distance spatiale des lieux. La diffusion de l’hôte s’inscrit dans des systèmes complexes et multiscalaires tissés dans la rencontre des espaces, des lieux, et des liens construits par les sociétés. Nous proposons une grille de lecture où les formes de la diffusion dans l’espace et le temps répondent des degrés de stabilité et d’instabilité de ces systèmes socio-spatiaux, façonnant ainsi des territoires inégalement vulnérables au risque d’émergence infectieuse. / The evolution of spatial relationships in the contemporary context of global changes and globalization promote disease emergence. In this study, we draw a geography of territorial vulnerabilities to the emergence of zoonotic risks. In southeastern Senegal, a changing rural periphery of West Africa, we address the issue of the spread of an invasive species and host of pathogens, the black rat (Rattus rattus). We argue that societies produce territorial systems that are unequally vulnerable to the spatial diffusion of the host.We evidence that the spaces of Southeastern Senegal and the spatial relationships among them are transformed under the action of multiple social actors. The spread of the black rat reflects these changes. Yet, the spatial characteristics of the invaded places (such as connectivity or centrality) as well as the spatial relationships among them are insufficient in understanding the spatial and temporal dynamics of the rodent invasion. Moreover, the spatial distribution of the black rat contradicts conventional models of hierarchical or contagious diffusion. The spatial diffusion of the host responds to spaces, places, and spatial links intimately woven by societies into complex and multiscale systems. We propose to understand the many forms of spatial diffusion as the response to the stability or instability of these socio-spatial systems, which then form territories unevenly vulnerable to the risk of disease emergence.

Les études menées dans cette thèse portent sur le rôle de la couleur dans l'attention visuelle. Nous avons tenté de comprendre l'influence de l'information couleur dans les vidéos sur les mouvements oculaire, afin d'intégrer les attributs couleur dans un modèle de saillance visuelle. Pour cela, nous avons analysé différentes caractéristiques des mouvements oculaires d'observateurs regardant librement des vidéos en deux conditions: couleur et niveaux de gris. Nous avons également comparé les régions principales de regard sur des vidéos en couleur avec celles en niveaux de gris. Il est apparu que les informations de couleur modifient légèrement les caractéristiques de mouvement oculaire comme la position de l'œil et la durée des fixations. Cependant, nous avons constaté que la couleur augmente le nombre de régions de regard. De plus, cet influence de la couleur s'accroît au cours du temps. En nous appuyant sur ces résultats, nous avons proposé une méthode de calcul des cartes de saillance couleur. Nous avons intégré ces cartes dans un modèle de saillance existant. / The studies conducted in this thesis focus on the role of colour in visual attention. We tried to understand the influence of colour information on the eye movements while observing videos, to incorporate colour information into a model of visual saliency. For this, we analysed different characteristics of eye movements of observers while freely watching videos in two conditions: colour and grayscale videos. We also have compared the main regions of regard of colour videos with those of grayscale. We observed that colour information influences only moderately, the eye movement characteristics such as the position of gaze and duration of fixations. However, we found that colour increases the number of the regions of interest in video stimuli. Moreover, this varies across time. Based on these observations, we proposed a method to compute colour saliency maps for videos. We have incorporated colour saliency maps in an existing model of saliency.

Les zones intertropicales sont caractérisées par des précipitations très variables dans l'espace et le temps qui peuvent produire sur une même région des conditions de sécheresse prolongées entrecoupées d'événements pluviométriques intenses. Ces extrêmes secs et humides peuvent provoquer des pénuries d’eau ou des inondations, mettant en péril des populations souvent très vulnérables aux aléas climatiques. C'est particulièrement le cas de l'Afrique de l'Ouest qui, dans un contexte de conditions sèches dominantes depuis les années 1970, subit ces deux dernières décennies un nombre croissant d'inondations. Face à un réchauffement climatique déjà bien réel, mais qui va se renforcer avec des conséquences sur le cycle de l'eau encore très incertaines, il est nécessaire de mieux comprendre comment la variabilité climatique – et en l’occurrence plus spécifiquement la variabilité pluviométrique, impacte la variabilité hydrologique. On dispose pour cela de modèles numériques de surface qui représentent de façon explicite les principaux processus intervenant dans les bilans d’eau. Ils doivent être alimentés par des champs de forçage pluviométrique à des résolutions suffisamment fines pour bien représenter les variabilités de petite échelle qui caractérisent les précipitations tropicales (résolution spatiale de quelques kilomètres et pas de temps horaire ou inférieur). De telles résolutions sont la plupart du temps incompatibles avec les échelles des données issues des réseaux pluviométriques nationaux en Afrique de l'Ouest (densité moyenne de 1 pluviomètre pour 10.000 km² au pas de temps journalier). Il existe de surcroît des zones entières qui sont peu ou mal couvertes du fait de conditions climatiques difficiles ou du manque de moyens des services météorologiques nationaux. Dans ce contexte, la télédétection satellite s'avère très utile, mais elle ne permet pas encore d’atteindre les résolutions mentionnées plus haut. Compte tenu de cette situation, la question de la sensibilité des modèles hydrologiques à la résolution des champs pluviométriques utilisés pour les forcer constitue un sujet important, assez peu abordé en tant que tel dans la littérature consacrée à l’utilisation des données satellitaires pour forcer des modèles hydrologiques.Cette thèse s’attache donc à traiter séquentiellement deux questions distinctes, mais souvent confondues : i) quel est l’impact de la dégradation de la résolution spatio-temporelle des champs de forçages pluviométriques sur la réponse d’un modèle hydrologique, et ce en supposant que ces champs sont dépourvus d’erreur en moyenne ; ii) comment les champs de pluie estimés par satellite, qui présentent de façon combinée des problèmes de résolution et de biais, influencent-ils la réponse hydrologique simulée?Le jeu de données utilisé pour l’étude est celui du site soudanien de l’observatoire AMMA-CATCH au Benin (bassin de l’Ouémé, 13150 km2). Le réseau de pluviographes de cet observatoire permet de calculer des champs de référence à très fine résolution (0.05° et 30 minutes), utilisés pour forcer le modèle hydrologique DHSVM et constituer ainsi des débits simulés de référence. A partir de là il est possible de procéder à des études de sensibilité dans les deux directions mentionnées ci-dessus. / Intertropical climates are characterized by a strong space-time variability of precipitation that can produce persistent dry spells and extreme rainfall events within the same region. These extreme climatic conditions directly impact water resources and flood occurrences, threatening populations that are highly vulnerable to natural hazards. This is especially the case in West Africa, where an increasing number of flood events has been reported over the last twenty years while the dry conditions that have started in the 1970's still prevail nowadays. While a significant climate warming is already observed in this region, there is more to come, with possible changes of the patterns of rainfall variability. It is thus of primary importance to better apprehend how sensitive is the hydrological response of West African catchments to small scale rainfall variability. Numerical models explicitly simulating the hydrological processes have already been tested and calibrated to represent the rainfall-runoff relationship of these catchments. They require high resolution (typically a few kilometers in space and one hour or less in time) rainfields as inputs, so as to account properly for the small scale variability of precipitation. However, this requirement is difficult to meet in a region where operational networks have a density which often does not exceed one gauge per 10000 km² and provide daily measurements only. Satellite remote sensing is consequently seen as a remedy to the shortcomings of ground monitoring, especially as it provides a continuous monitoring in space and time, but satellite rainfall products are still far from reaching the high space-time resolution mentioned above. In such a context, the sensitivity of hydrological models to the resolution of their forcing rainfields is an important topic, rarely tackled as such in the literature dealing with hydrological modeling based on satellite data.This PHD thesis thus focus on two related questions : i) how degrading the space-time resolution of forcing rainfields is influencing the response of hydrologic models, assuming that this degradation of the resolution has no influence on the biases ? ; ii) what are the consequences of using satellite rainfall products – which combine low resolution and bias problems – for simulating the response of catchments in tropical regions?To that end the AMMA-CATCH data set of the Ouémé catchment (13150 km2) in Benin is used. The high density recording raingauge network allows the computation of fine resolution rainfields (0.05°; 30 minutes), used as inputs to the DHSVM hydrological model, providing reference series of river flows at the outlet of the catchment.

Découvrir les environs tout en marchant à l'aide d'un appareil mobile est désormais possible en associant les nouvelles technologies telles que la réalité augmentée (RA) et les services basés sur la localisation. De nombreuses applications mobiles ont été conçues à cet effet récemment. Les environs d'un utilisateur en mouvement sont présentés sur l'écran de son appareil mobile en utilisant les données de géo-localisation et elle peut interagir avec son environnement grâce à une couche d'information numérique superposée sur la scène capturée. Toutefois, la quantité d'informations géo-référencées produites et accessibles augmentant chaque jour, il y a un besoin croissant d'une approche générique qui vise à présenter l'information de manière structurée et adaptée aux différents domaines d'application et à la diversité des profils des utilisateurs.Notre travail se concentre sur la définition d'un modèle de données pour les objets 3D destiné à être intégré dans des applications de RA mobiles. Le modèle de données que nous proposons donne accès à l'information spatio-temporelle et thématique disponible sur les objets du monde réel. Alors que la réalité augmentée semble être bien adaptée pour la recherche d'informations à partir de la localisation, la plupart des approches basées sur la RA se concentre sur des scénarios spécifiques à un domaine d'application. D'autre part, le nuage des données ouvertes et liées (LOD Cloud en anglais) est un ensemble en constante extension de données structurées et publiées sur le Web. Il contient donc de grandes quantités d'informations à références spatio-temporelles qui peuvent être exploitées par les applications mobiles et présentées en utilisant la RA pour favoriser l'interaction. Dans notre recherche, ce nuage du Web des Données sert de source principale d'information au cours de l'expérience de découverte des environs à l'aide de la RA proposée à l'utilisateur.À cette fin, nous publions sur le Web les objets 3D correspondant aux objets du monde réel en utilisant notre modèle de données, ce qui permet de les lier avec le nuage du Web des Données. De fait, un objet du monde réel peut être représenté selon trois dimensions d'information : thématique (qui décrit les rôles ou fonctions de l'objet), spatiale (à travers sa géométrie 3D), et temporelle (par la période qui correspond à son existence). De plus, chaque changement dans la vie d'un objet du monde réel est représenté dans le modèle par des informations sémantiques. En conséquence, sur son appareil mobile, l'utilisateur visualise une vue de RA construite avec des modèles 3D légers et transparents. Il peut interagir avec ces objets de RA afin d'accéder aux informations relatives aux objets du monde réel correspondants qui se trouvent aux alentours et vers lesquels il pointe son téléphone mobile. Ces objets de RA permettent à l'utilisateur de construire mentalement la relation référentielle entre les objets virtuels et réels, tandis que le développeur de l'application mobile peut créer des expériences basées sur des thématiques différentes disponibles à travers sur le nuage du Web des Données (architecture, histoire, gastronomie, loisirs, etc.).En nous appuyant sur cette base de connaissances conceptualisée, nous proposons une architecture appelée ARCAMA-3D (Réalité Augmentée et 3D pour les applications mobiles sensibles au contexte), dont les modules permettent aux concepteurs et développeurs de créer leurs propres applications de RA pour différents domaines en étant en mesure d'étendre le modèle de données, de lier les modèles 3D avec d'autres ensembles de données ouvertes et liées disponibles dans le nuage, et d'alimenter ces applications de découverte à partir de sources de données spécifiques. Notre proposition est illustrée sur le cas d'étude que constitue le Monastère Royal de Brou, en France, à travers un scénario de cas d'utilisation pour un utilisateur visitant ce monument historique. / Discovering the surroundings while walking using a mobile device is now possible by coupling new technologies such as Augmented Reality (AR) and location-based services. Many mobile applications have been designed for that purpose recently. The surroundings of the user are presented on the screen of her mobile device using the location data and she can interact with her environment through a digital information layer superimposed on the captured scene. However, since the amount of geo-referenced information increases every day, there is a growing need for a generic approach that aims at presenting information in a structured manner and adapted to different application domains and users profiles.Our work focuses on the definition of a data model for 3D objects to be used in mobile AR applications. The data model we propose prioritizes access to available spatiotemporal and thematic information about real-world objects. While Augmented Reality appears to be well-suited for searching location-based information, most of the AR approaches focus on domain specific scenarios and we observe that there is no generic data model dedicated to information search and discovery that could be re-used in various AR applications. On the other hand, Linked Open Data (LOD) cloud is an ever-growing set of structured and interlinked datasets published on the Web. It contains vast amounts of spatiotemporal information that can be exploited by location-based mobile applications and presented using AR for fostering interaction. In our research, the LOD cloud serves as a basis for information retrieval during the AR experience of the user.For this purpose, we first publish 3D objects that correspond to real-world objects (buildings, monuments, etc.) on the Web by using our data model and interlink them with data sources on the LOD cloud. Then, using our data model, any real-world object can be represented by three informational dimensions: themes (describing the roles or functions of this object), space (through its 3D geometry), and time (the period linked to its existence). Each change in the life of a real-world object is represented in the model by semantic information following the LOD publishing principles. This allows a binding between the content of our data model and the LOD cloud. As a consequence, on her mobile device, the user visualizes an AR view built with light and transparent 3D models. She can interact with these AR objects in order to access to information related to the corresponding real-world objects of her surroundings she is pointing at. These AR objects allow the user to mentally construct the referential relationships between virtual and real-world objects, while the mobile application developer can create experiences based on different concepts found on the cloud (thematic and temporal concepts, etc.). This way, the LOD cloud, as a growing and updated structured source of semantic data, becomes the main source of information and facilitates knowledge discovery in AR applications.Using this conceptualized knowledge base, we propose our architecture, called ARCAMA-3D (Augmented Reality for Context Aware Mobile Applications with 3D), whose modules allow application designers and developers to create their own AR applications for different domains by being able to extend the data model, bind 3D models with other data sources on the LOD cloud, cover a selected part of LOD and feed their application only with these specific data sources. We develop our ideas working on the case study of the Royal Monastery of Brou, in France, and implement a use case scenario for a user visiting the monastery.

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-08-30T17:25:22Z No. of bitstreams: 1 CAIO LIBÂNIO MELO JERÔNIMO – DISSERTAÇÃO (PPGCC) 2017.pdf: 4821943 bytes, checksum: 615dc29730ed480c902a5496dce5492f (MD5) / Made available in DSpace on 2018-08-30T17:25:22Z (GMT). No. of bitstreams: 1 CAIO LIBÂNIO MELO JERÔNIMO – DISSERTAÇÃO (PPGCC) 2017.pdf: 4821943 bytes, checksum: 615dc29730ed480c902a5496dce5492f (MD5) Previous issue date: 2017-07-07 / Capes / A demanda constante por melhorias na qualidade de vida dos habitantes das grandes cidades, somado à crescente urbanização desses centros, torna imprescindível a utilização de meios tecnológicos para um melhor entendimento da dinâmica dos centros urbanos e como seus habitantes interagem nesses ambientes. Nesse sentido, o aumento na utilização de dispositivos eletrônicos equipados com sistemas GPS e o constante anseio da humanidade por comunicação e, mais atualmente, por conexão à internet, vem criando novas oportunidades de estudo e também grandes desafios, especialmente no que tange a grande quantidade de dados gerados pelas redes sociais. Diversas pesquisas vêm utilizando esses dados para realizar estudos que buscam compreender traços do comportamento humano, especialmente no que diz respeito à mobilidade urbana e trajetórias. Porém, grande parte das pesquisas que utilizam dados georreferenciados se restringem às dimensões espaciais e temporais, desconsiderando outros aspectos que podem influenciar na mobilidade humana. Este trabalho propõe um método computacional capaz de extrair padrões de mobilidade oriundos de mensagens georreferenciadas de redes sociais e correlacioná-los com indicadores sociais, econômicos e demográficos fornecidos por órgãos governamentais, buscando assim, analisar quais possíveis fatores poderiam exercer alguma influência sobre a mobilidade dos moradores de uma grande cidade. Para validar o método proposto, foram utilizadas mensagens postadas no Twitter e um conjunto de indicadores sociais, ambos oriundos da cidade de Londres. Os resultados mostraram a existência de correlações entre padrões de mobilidade e indicadores sociais, especialmente os relacionados com condições de emprego e renda, como também com características étnico-religiosas dos indivíduos em estudo. / The constant need for improvements in life quality of inhabitants of big cities, together with the increasing urbanization of these centers, demands the use of technological means for a better understanding of the dynamics of urban centers and how their inhabitants interact in these environments. In this sense, the adoption of electronic devices equipped with GPS systems, the human need for communication and, more recently, for Internet connection, have brought new research opportunities and great challenges, especially due to the huge amount of data generated by social networks. Several studies have used this data to carry out research that seek to understand traces of human behavior, especially with respect to urban mobility and trajectories. However, much of the research that uses georeferenced data are restricted to spatial and temporal dimensions, disregarding other aspects that may influence human mobility. This work proposes a model capable of extracting mobility patterns from georeferenced messages of social networks and correlating them with social, economic and demographic indicators provided by government agencies, seeking to analyze which factors may impact in urban mobility. To evaluate the model, we used messages posted on Twitter and a set of social indicators, both related to the city of London. The results revealed the existence of correlations between mobility patterns and social indicators, especially those related to employment and income conditions, as well as ethnic and religious characteristics of the individuals under study.