Retinal Vessel Segmentation Based on Adaptive Random Sampling

International audienceThis paper presents a method for the extraction of blood vessels from fundus images. The proposed method is an unsupervised learning method which can automatically segment retinal blood vessels based on an adaptive random sampling algorithm. This algorithm consists in taking an adequate number of random samples in fundus images, and all the samples are contracted to the position of the blood vessels, then the retinal vessels will be revealed. The basic algorithm framework is presented in this paper and several preliminary experiments validate the feasibility and effectiveness of the proposed method

Computing with bacterial constituents, cells and populations: from bioputing to bactoputing

The relevance of biological materials and processes to computing—aliasbioputing—has been explored for decades. These materials include DNA, RNA and proteins, while the processes include transcription, translation, signal transduction and regulation. Recently, the use of bacteria themselves as living computers has been explored but this use generally falls within the classical paradigm of computing. Computer scientists, however, have a variety of problems to which they seek solutions, while microbiologists are having new insights into the problems bacteria are solving and how they are solving them. Here, we envisage that bacteria might be used for new sorts of computing. These could be based on the capacity of bacteria to grow, move and adapt to a myriad different fickle environments both as individuals and as populations of bacteria plus bacteriophage. New principles might be based on the way that bacteria explore phenotype space via hyperstructure dynamics and the fundamental nature of the cell cycle. This computing might even extend to developing a high level language appropriate to using populations of bacteria and bacteriophage. Here, we offer a speculative tour of what we term bactoputing, namely the use of the natural behaviour of bacteria for calculating

Modélisation automatique de géo-environnements naturels et multi-urbains

Nous présentons de nouveaux modèles de génération de terrains naturels et urbains que nous nommons géo-environnements. Ces modèles ont tous été développés, testés et optimisés sur les ordinateurs du département d'Informatique de l'Université de Paris 8 à Saint-Denis. Nos modèles statistiques ont permis d'obtenir des gains de temps allant jusqu'à 17000% en comparaison avec la meilleure méthode connue dans un problème de reconstruction de données satellites à partir d'échantillons. Au delà de l'efficacité, nos algorithmes donnent les résultats suivants : un bon degré de variabilité des données initiales traitées et la capacité de générer intégralement des modèles réalistes de paysages érodés ; à partir d'une méthode inédite, la méthode des écoulements, nous engendrons des modèles-squelette décrivant des lignes de crêtes et des bassins versants sous la forme de contraintes locales. Pour les environnements urbains, nous proposons un processus générant un plan d'occupation des sols à partir d'un modèle de terrain. Nous générons successivement la carte de densité de population, les emplacements et les dimensions des sites d'agglomération et enfin le réseau routier les reliant en considérant les données du relief. Nous proposons enfin des extensions essentielles pour les champs d'application des domaines connexes : notre algorithme fractal peut s'appliquer à la reconstruction d'un modèle de terrain à partir de données partielles, ces données sont soit sous-échantillonnées, soit squelettisées puis amplifiées via notre modèle fractal ; nous proposons également des applications dans le domaine de la reconstruction de photographies et en rendu non-photoréaliste.We present new models for generating natural terrains and urban environments. Our fractal algorithm manages local or global constraints: we can impose elevations and modify the global aspect of the generated models. We also generate fully realistic models of eroded landscapes: we propose a new method that generates skeleton models describing ridge lines and river networks. These models are used as input constraints of our fractal algorithm. This method is also used in data reconstruction from scattered elevation datasets. Our method is up to 17000% faster than the best known one. For urban environments, we propose a urbanization process that generates development plans by using only terrain models as input data. We successively generate population density maps, compute dimensions and locations of city sites according to a given distribution and then generate road networks that connect city sites according to the terrain relief. Finally, We present applications of our fractal model to surface reconstruction either from downsampled data or contour lines data. This application is extended to photograph reconstruction giving non-photo-realistic renderings. We also combine our fractal model and our urbanization process to entirely generate natural and urban environments.ST DENIS-BU PARIS8 (930662101) / SudocSudocFranceF

An evolutionary supported multi agent system methodology for computer aided cellular architectural design

Nous proposons un cadre méthodologique de conception architecturale qui utilise opérations et outils de l'intelligence artificielle: nous proposons, dans cette étude, de matérialiser un espace architectural a priori imaginaire et global par des opérations d'instanciations et de réifications essentiellement locales de conception cellulaire. L'Espace Architecte (EA) est un espace imaginaire. L'édifice auquel cet espace peut correspondre, étant bien réel, est une transcription matérielle des propriétés de cet EA, et aussi la résultante de contraintes, de choix, de pressions physiques et sociales. Cette résultante est l'aboutissement et l'effet d'opérations rassemblées en structure. Les opérations, qui sont dotées de propriétés formelles et algorithmiques, constituent les outils de matérialisation d'un EA. Les structures opératives, vu la complexité des EA imaginaires à réaliser mettent en jeu pour l'instant une informatique de modélisation et d'optimisation qui relève clairement de l'intelligence artificielle d'aujourd'hui: heuristiques, monte-carlos, sélections et évolutions artificielles, multi-agences. Nous proposons un répertoire et une mise en ordre de ces méthodes et leur applications à la conception en architecture. Nous examinons à cette occasion les aspects de l'histoire de l'architecture qui mènent logiquement vers notre approche. Dans l'introduction, nous présentons la problématique (les origines, le but, les limites et les usages) de la méthode proposée. Dans le premier chapitre, nous présentons un système de multi-agences, supporté par une méthode évolutionniste. Dans le second chapitre, nous décrivons une interface architecturale, qui s'interpose entre le système de multi-agences et l'Architecte utilisateur. Dans le troisième chapitre, nous décrivons les principes de l'histoire et de la théorie de l'architecture. Dans le quatrième chapitre, nous répondons à la question "pourquoi l'Architecte a besoin de concepts et méthodes de l'intelligence artificielle?", en parcourant brièvement les théories, méthodes et applications associées. Finalement, dans le cinquième chapitre, en conclusion, nous réexaminons la plus grande part des plans et maquettes présentées aux chapitres précédents qui pourront être examinés cette fois à la lumière de nos propositions. On constatera qu'une partie importante de nos exemples concernent la conception de logements et de parties critiques d'iceux: cuisines, salles d'eau, ce genre de fonctions: nous sommes convaincus que l'architecture formalisée doit se donner pour but de résoudre avant tout des problèmes pratiques. Enfin, c'est très délibérément, que nous avons, dans le cadre de cette thèse, décidé de placer notre contribution personnelle avant l'histoire du domaine, qui n'a jamais cessé de figurer en arrière-fond de notre travail.We propose a methodological framework of architectural design which uses operations and tools of artificial intelligence: we propose, in this study, to materialize an a priori imaginary and global architectural space by primarily local operations of instantiations and reifications of cellular design. The Architect Space (AS) is an imaginary space. The building to which this space can corresponds, being quite real, is a material transcription of the properties of this AS, and also the resultant of constraints, choices, and physical and social pressures. This resultant is the achievement and the effect of operations gathered as a structure. These operations, which are equipped with formal and algorithmic properties, constitute the tools for materialization of an AS. The operative structures, considering the complexity of the imaginary AS to materialize involve as for now a data processing of modeling and optimizations which concerns clearly the artificial intelligence today: heuristics, monte-carlos, artificial selections and evolutions, multi-agents. We propose a repertory and an ordering of these methods and their applications to the architectural design. We examine on this occasion the aspects of the history of architecture which carry out logically towards our approach. In the introduction, we present the problematic (origins, goal, limits and uses) of the proposed method. In chapter 1, we present a multi agent system, supported by an evolutionary method. In chapter 2, we describe an architectural interface, which interposes between the multi agent system and the Architect user. In chapter 3, we describe the principles of history of theory of architecture. In chapter 4, we answer the question "why Architect needs the concepts and methods of the artificial intelligence?", by briefly traversing the associated theories, methods and application. Finally concluding, in chapter 5, we re-examine the greatest part of the plans and models presented at the preceding chapters which could be examined this time in the light of our proposals. One will note that a significant part of our examples relate to the design of residences and their critical parts: kitchens, bathrooms, this sort of functions: we are convinced that formal architecture must aim to solve the practical problems above all. Finally, it is very deliberately, that we have decided, within the framework of this thesis, to place our personal contribution before the history of the field, which never ceased appearing in innermost depth of our work.ST DENIS-BU PARIS8 (930662101) / SudocSudocFranceF

Contributions à l'optimisation des ressources énergétiques dans les réseaux de processeurs à capteurs

Face aux problèmes d'automonie énergétique, de durée de fonctionnement, de sûreté d'acquisition des données des réseaux de capteurs, nous proposons deux solutions optimisantes : la première est un outil original de description de programmes TinyOS et d'économie d'énergie consommée. Cet outil nous permet de déterminer l'attribution optimisée de fréquences pour l'exécution des différentes tâches d'une application d'un réseau de capteurs, par simple recompilation du code d'une application existante. la seconde est la transposition aux réseaux de capteurs des outils d'autocorrection utilisés dans les sondes spatiales. L'intégrité de vastes ensembles de données transmis à grande distance, nous la transposons à l'économie d'énergie consommée et de puissance de transmission liées à la certitude de ne pas avoir à retransmettre des données toujours de faible taille entre processeurs capteurs d'un réseau.In order to solve the problem related to lifetime and safety in wireless sensor networks, we propose the following solutions : The first one is an original tool for describing TinyOS programs and for harvesting sensors energy. Our tool allows us to optimize the execution frequency of applications at compile time, in order to reduce sensor energy consumption. The second one is the usage of forward error control techniques used in spacecraft. We exploit the fact that this technique requires neither acknoledgment nor data retransmission when errors occur.ST DENIS-BU PARIS8 (930662101) / SudocSudocFranceF

From bioputing to bactoputing: computing with bacteria

The relevance of certain biological materials and processes to computing or bioputing has been explored for decades. These materials include DNA, RNA, enzymes and other proteins whilst the processes include transcription and translation (as well as the control of these processes by protein and by small RNA) and signal transduction. Recently, other directions have been envisaged using bacteria themselves as living computers. Generally, these uses of bacteria fall within the classical paradigm of computing. Computer scientists, however, have a variety of problems to which they seek solutions whilst microbiologists are having new insights into the problems bacteria are solving and how they are solving them. Here, we envisage that bacteria might be used for new sorts of computing. These might be based on the capacity of bacteria to grow, move and adapt to a myriad different fickle environments as both individuals and as populations of both bacteria and bacteriophage. This new computing may extend to developing a new high level language appropriate to using populations of bacteria and bacteriophage. Such new principles might be based on the way that bacteria explore phenotype space via hyperstructure dynamics and the fundamental nature of the cell cycle. Here we offer a speculative tour of what we term bactoputing, namely the use of the natural behaviour of bacteria and other cells for calculating

From bioputing to bactoputing: computing with bacteria

The relevance of certain biological materials and processes to computing or bioputing has been explored for decades. These materials include DNA, RNA, enzymes and other proteins whilst the processes include transcription and translation (as well as the control of these processes by protein and by small RNA) and signal transduction. Recently, other directions have been envisaged using bacteria themselves as living computers. Generally, these uses of bacteria fall within the classical paradigm of computing. Computer scientists, however, have a variety of problems to which they seek solutions whilst microbiologists are having new insights into the problems bacteria are solving and how they are solving them. Here, we envisage that bacteria might be used for new sorts of computing. These might be based on the capacity of bacteria to grow, move and adapt to a myriad different fickle environments as both individuals and as populations of both bacteria and bacteriophage. This new computing may extend to developing a new high level language appropriate to using populations of bacteria and bacteriophage. Such new principles might be based on the way that bacteria explore phenotype space via hyperstructure dynamics and the fundamental nature of the cell cycle. Here we offer a speculative tour of what we term bactoputing, namely the use of the natural behaviour of bacteria and other cells for calculating

Computing with bacterial constituents, cells and populations: from bioputing to bactoputing

International audienc