Object region detection plays a vital role in many domains ranging from self-driving cars to lane detection, which heavily involves the task of object detection. Improving the performance of object region detection approaches is of great importance and therefore is an active ongoing research in Computer Vision. Traditional sliding window paradigm has been widely used to identify hundreds of thousands of windows (covering different scales, angles, and aspect ratios for objects) before the classification step. However, it is not only computationally expensive but also produces relatively low accuracy in terms of the classifier output by providing many negative samples. Object detection proposals, as discussed in detail in [19, 20], tackle these issues by filtering the windows using different features in the image before passing them to the classifier. This filtering process helps to control the quality as well as the quantity of the windows. EdgeBox is one of the most effective proposal detection approaches that focuses on the presence of dense edges in an image to identify quality proposal windows. This thesis proposes an innovative approach that improves the accuracy of the EdgeBox approach. The improved approach uses both the color properties and the corner information from an image along with the edge information to evaluate the candidate windows. We also describe two variations of the proposed approach. Our extensive experimental results on the Visual Object Classification (VOC) [29,30] dataset clearly demonstrate the effectiveness of the proposed approach together with its two variances to improve the accuracy of the EdgeBox approach.

Cette thèse est dédiée à l’analyse du retard (de calcul ou induit par la communication), qui représente un des paramètres sensibles, et qui doit être pris en compte, pour la mise en œuvre de la Commande Prédictive en temps réel d’un processus dynamique. Dans la première partie, nous avons abordé le problème d’existence des ensembles D-invariants et avons fourni par la suite des conditions nécessaires et/ou suffisantes pour l’existence de ces ensembles. En outre, nous avons détaillé quelques nouvelles idées sur la construction des ensembles D-invariants en utilisant des algorithmes itératifs et d’autres algorithmes basés sur des techniques d’optimisation à deux niveaux. La seconde partie a été consacrée à l’étude du problème de robustesse des systèmes linéaires discrets affectés par un retard variable en boucle fermée avec un contrôleur affine par morceaux défini sur une partition polyédrale de l’espace d’état. L’étude a porté sur l’analyse de la fragilité d’une telle loi commande en présence du retard dans la boucle. Nous avons décrit les marges d’invariance robustes définies comme étant le plus grand sous-ensemble de l’incertitude paramétrique pour lequel l’invariance positive est garantie par rapport à la dynamique en boucle fermée en présence du retard. La dernière partie de cette thèse s’est articulée autour de la conception des lois de commande prédictives avec un attention particulière aux modèles linéaires discrets décrivant des dynamiques affectées par des contraintes en présence du retard. Nous avons proposé plusieurs méthodes offrant différentes solutions au problème de stabilisation locale sans contrainte. Afin d’assurer la stabilité et de garantir la satisfaction des contraintes, nous avons exploité le concept d’invariance et à l’aide du formalisme "ensemble terminal-coût terminal", un problème d’optimisation a été formulé où les états sont forcés d’atteindre l’ensemble maximal admissible d’états retardés/D-invariant à la fin de l’horizon de prédiction. Enfin, nous avons étudié le problème de stabilisation des systèmes continus commandés en réseau soumis à des retards incertains et éventuellement variant dans le temps. Nous avons montré que les ensembles λ-D-contractifs peuvent être utilisés comme ensembles cibles où la stratégie de commande consiste en un simple problème de programmation linéaire ’LP’ qui peut être résolu en ligne. / The research conducted in this thesis has been focusing on Model Predictive Control (MPC) and the implication of network induced time-varying delays. We have addressed, in the first part of this manuscript, the existence problem and the algorithmic computation of positive invariant sets in the state space of the original discrete delay difference equation. The second part of these thesis has been devoted to the study of the robustness problem for a specific class of dynamical systems, namely the piecewise affine systems, defined over a polyhedral partition of the state space in the presence of variable input delay. The starting point was the construction of a predictive control law which guarantees the existence of a non-empty robust positive invariant set with respect to the closed-loop dynamic. The variable delay inducing in fact a model uncertainty, the objective was to describe the robust invariance margins defined as the largest subset of the parametric uncertainty for which the positive invariance is guaranteed with respect to the closed-loop dynamics in the presence of small and large delays. The last part has been dedicated to Model Predictive Control design with a specific attention to linear discrete time-delay models affected by input/state constraints. The starting point in the analysis was the design of a local stabilizing control law using different feedback structures. We proposed several design methods offering different solutions to the local unconstrained stabilization problem. In order to ensure stability and guarantee input and state constraints satisfaction of the moving horizon controller, the concept of positive invariance related to time-delay systems was exploited. Using the "terminal setterminal cost" design, the states were forced to attain the maximal delayed-state admissible set at the end of the prediction horizon. Finally, we have investigated the stabilization problem of Networked Control Systems ’NCSs’ subject to uncertain, possibly time-varying, network-induced delays. We showed that λ-D-contractive sets can be used as a target sets in a set induced Lyapunov function control fashion where a simple Linear Programming ’LP’ problem is required to be solved at each sampling instance.

京都大学 / 0048 / 新制・論文博士 / 博士(医学) / 乙第12957号 / 論医博第2099号 / 新制||医||1011(附属図書館) / 32356 / 京都大学大学院医学研究科医学専攻 / (主査)教授 生田 宏一, 教授 岩井 一宏, 教授 椛島 健治 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・論文博士 / 博士(医学) / 乙第12978号 / 論医博第2104号 / 新制||医||1012(附属図書館) / 32448 / 京都大学大学院医学研究科医学専攻 / (主査)教授 三森 経世, 教授 椛島 健治, 教授 生田 宏一 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(人間・環境学) / 甲第19797号 / 人博第768号 / 新制||人||185(附属図書館) / 27||人博||768(吉田南総合図書館) / 32833 / 京都大学大学院人間・環境学研究科共生人間学専攻 / (主査)教授 齋藤 治之, 教授 壇辻 正剛, 准教授 谷口 一美 / 学位規則第4条第1項該当 / Doctor of Human and Environmental Studies / Kyoto University / DGAM

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This thesis presents methods for robust precision landing of unmanned air vehicles (UAVs) on platforms at sea. Localization methods are proposed for UAV-to-boat state estimation for systems that employ real- time kinematic (RTK) global navigation satellite system (GNSS) and vision sensors. Solutions for GNSS-only are first presented, followed by the fusion of GNSS and vision. The important problem of sensor intrinsic calibration is solved with a novel offline batch estimation approach. Hardware results are presented for all methods. Our calibration of GNSS-to-camera is shown to estimate sensor offsets with millimeter level accuracy. Localization systems are combined with custom state machines that manage the landing attempt via a novel descent cone. This conical threshold enforces a safe and accurate landing. Our landing methods are demonstrated in real-world experiments and achieve consistent accurate landings with error below 10 cm. The fusion of camera and RTK is shown to produce a robust landing system with redundant localization sources.

The Lyme disease spirochete Borrelia burgdorferi is the only known human pathogen that directly activates invariant natural killer T (iNKT) cells. The number and activation kinetics of iNKT cells vary greatly among different strains of mice. Here, we report the role of the iNKT cell response in the pathogenesis of Lyme disease using C57BL/6 (B6) mice, a strain with optimal iNKT cell activation that is resistant to the development of spirochetal-induced inflammation. During experimental infection of B6 mice with B. burgdorferi , iNKT cells localize to the inflamed heart where they are activated by CD1d-expressing macrophages. Activation of iNKT cells in vivo results in the production of IFNγ, which we demonstrate controls the severity of murine Lyme carditis by at least two mechanisms. First, IFNγ greatly enhances the recognition of B. burgdorferi by macrophages, leading to increased phagocytosis of the spirochete. Secondly, IFNγ activation of macrophages increases the surface expression of CD1d, thereby facilitating further iNKT activation. Collectively, our data demonstrate that in the resistant background, B6, iNKT cells modulate acute murine Lyme carditis through the action of IFNγ, which appears to self-renew through a positive feedback loop during infection. Inflammation during infection with B. burgdorferi is dependent on the ability of the spirochete to evade local mechanisms of clearance. Even though macrophages are the main infiltrating cell during Lyme carditis, the identification of a receptor capable of mediating phagocytosis of B. burgdorferi has been elusive. Here, we demonstrate that the integrin CR3 is able to mediate binding to the spirochete and facilitate phagocytosis in a complement-dependent and independent manner. Expression of CR3, but not CR4, in CHO cells markedly enhanced their capacity to interact with B. burgdorferi , in the absence and presence of complement opsonization. Furthermore, the interaction between CR3 and B. burgdorferi is dependent on the metal-ion-dependent adhesion site (MIDAS) and could be blocked with EDTA. Inhibition of CR3 with blocking antibody was able to completely abrogate phagocytosis of B. burgdorferi by the macrophage-like RAW264.7 cells and partially block uptake by bone marrow-derived macrophages (BMMs), a finding that was recapitulated with CD11b-deficient BMMs. We further show that activation with recombinant IFNγ increases the transcription of CD11b and CD18, which correlates with increased surface expression of CR3, and that the effect of IFNγ on the phagocytosis of B. burgdorferi is circumscribed to CR3 activity, because inhibition of CR3 is able to completely diminish the effect of IFNγ on the phagocytosis of the B. burgdorferi . Lastly, our results demonstrate that CR3 is a negative regulator of proinflammatory cytokine induction in macrophages responding to B. burgdorferi . Overall, our data demonstrate roles for CR3 in the binding, phagocytosis and proinflammatory cytokine elicited by B. burgdorferi and shed light on the role of IFNγ in mediating the clearance of the spirochete during Lyme disease.

Ensuring constraint satisfaction in large-scale systems with hard constraints is vital in many safety critical systems. The challenge is to design controllers that are efficiently synthesized offline, easily implementable online, and provide formal correctness guarantees. We take a divide and conquer approach to design controllers for reachability and infinite-time/finite-time constraint satisfaction control problems given large-scale interconnected linear systems with polyhedral constraints on states, controls, and disturbances. Such systems are made of small subsystems with coupled dynamics. Our goals are to design controllers that are i) fully compositional and ii) decentralized, such that online implementation requires only local state information. We treat the couplings among the subsystems as additional disturbances and use assume-guarantee (AG) contracts to characterize these disturbance sets. For each subsystem, we design and implement a robust controller locally, subject to its own constraints and contracts. Our main contribution is a method to derive the contracts via a novel parameterization, and a corresponding potential function that characterizes the distance to the correct composition of controllers and contracts, where all contracts are held. We show that the potential function is convex in the contract parameters. This enables the subsystems to negotiate the contracts with the gradient information from the dual of their local synthesis optimization problems in a distributed way, facilitating compositional control synthesis that scales to large systems. We then incorporate Signal Temporal Logic (STL) specifications into our formulation. We develop a decentralized control method for a network of perturbed linear systems with dynamical couplings subject to STL specifications. We first transform the STL requirements into set containment problems, then we develop controllers to solve these problems. The set containment requirements and parameterized contracts are added to the subsystems’ constraints. We introduce a centralized optimization problem to derive the contracts, reachability tubes, and decentralized closed-loop control laws. We show that, when the STL formula is separable with respect to the subsystems, the centralized optimization problem can be solved in a distributed way, which scales to large systems. We present formal theoretical guarantees on robustness of STL satisfaction. We present numerical examples, including scalability studies on systems with tens of thousands of dimensions, and case studies on applying our method to a distributed Model Predictive Control (MPC) problem in a power system. / 2024-01-16T00:00:00Z