8 research outputs found

    On Clustering in Sensor Networks

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    Recent Advances in Multi Robot Systems

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    To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

    Methods for multilevel analysis and visualisation of geographical networks

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    Recent Advances in Signal Processing

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    The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

    Sensors and Systems for Indoor Positioning

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    This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications

    Predicting and characterising protein-protein complexes

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    Macromolecular interactions play a key role in all life processes. The construction and annotation of protein interaction networks is pivotal for the understanding of these processes, and how their perturbation leads to disease. However the extent of the human interactome and the limitations of the experimental techniques which can be brought to bear upon it necessitate theoretical approaches. Presented here are computational investigations into the interactions between biological macromolecules, focusing on the structural prediction of interactions, docking, and their kinetic and thermodynamic characterisation via empirical functions. Firstly, the use of normal modes in docking is investigated. Vibrational analysis of proteins are shown to indicate the motions which proteins are intrinsically disposed to undertake, and the use of this information to model flexible deformations upon protein-protein binding is evaluated. Subsequently SwarmDock, a docking algorithm which models flexibility as a linear combination of normal modes, is presented and benchmarked on a wide variety of test cases. This algorithm utilises state of the art energy functions and metaheuristics to navigate the free energy landscape. Information derived from Langevin dynamics simulations of encounter complex formation in the crowded cytosolic environment can be incorporated into SwarmDock and enhances its performance. Finally, a benchmark of binding free energies derived from the literature is presented. For this benchmark, a large number of molecular descriptors are derived. Machine learning methods are then applied to these in order to derive empirical binding free energy, association rate and dissociation rate functions which take account of the conformational changes which occur upon complexation

    Applications et services DTN pour flotte collaborative de drones

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    Les travaux présentés dans cette thèse effectuée au LaBRI portent sur la mise en place d une flotte de drones et le portage sur celle-ci d applications collaboratives distribuées utilisant des communications asynchrones non sûres. Ces applications sont formalisées grâce au modèle de réétiquetage de graphes Asynchronous Dynamicity Aware Graph Relabeling System (ADAGRS) que nous proposons. Au delà des contributions théoriques, ces travaux ont débouché sur la mise en place du démonstrateur CARUS dans lequel cinq drones se partagent la surveillance d'une grille de 15 points d incidents potentiels (au sol).Lorsqu un drone détecte un incident, il s'en rapproche pour le traiter. Le reste de la flotte doit alors prendre en charge les points que ce drone ne traite plus.Les réorganisations nécessaires de la flotte se font en totale autonomie vis-à-vis du sol et sous hypothèse de perte éventuelle de drones et de messages.The work presented in this thesis, carried out at LaBRI, deals with the set up of a fleet of UAVs and the porting on it of distributed collaborative applications that use unsafe asynchronous communications. These applications are modeled with Asynchronous Dynamicity Aware Graph Relabeling System (ADAGRS), the formal model based on graph relabellings that we propose.Beyond the theoretical contributions, this work led to the development of the CARUS demonstrator in which five UAVs share the supervision of a grid of 15 points of potential ground incidents.When a UAV detects an incident, it comes close to it in order to deal with it. The rest of the fleet must then take care of the points that this UAV no longer visits.The necessary reorganizations of the fleet are done in total autonomy with respect to the ground and under the hypothesis of possible loss of UAVs and messages.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF
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