Dissertations / Theses on the topic 'Connectivité des graphes'
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Kang, Haiyan. "Arêtes suppressibles, cycles et connectivité." Paris 11, 2010. http://www.theses.fr/2010PA112060.
Full textLet G be a k-connected graph and e=uv an edge of G. By G/e we denote the graph obtained from G by deleting the vertices u,v and adding a new vertex v_e such that v_e is adjacent to all the former neighbors of u and v. If G/e is still k-connected, then e is called a k-contractible edge. The first part of the thesis studies a property of a contractible edge in k-connected triangle-free graphs. Let G be a k-connected graph, and let e be an edge of G. Let GӨe denote the graph obtained from G by the following operation: (1) delete e from G to get G-e; (2) for any end vertex of e with degree k-1, say x, delete x, and then add edges between any pair of non-adjacent vertices in N_{G-e}(x). If GӨe is k-connected, then e is said to be a removable edge of G. The second part of the thesis investigates the distribution of removable edges in 3-connected graphs or 5-connected graphs. In addition, we confirm Thomassen’s conjecture for two classes of 3-connected graphs with bounds of removable edges on or off a longest cycle. The last part of the thesis is devoted to the prism cyclability of graphs. The prism over a graph G is the Cartesian product GK_2 of G with the complete graph K_2. G is said to be prism hamiltonian if GK_2 is hamiltonian. We say that a set H V(G) of vertices is cyclable in G if there is a cycle C in G containing all vertices of H. For H V(G), we say that H is prism cyclable in GK_2 if H∪H' where H' is the copy of H is cyclable in GK_2. We extend Ozeki’s result on prism hamiltonicity to prism cyclability of S. It is also argued for claw-free graphs, the bound can be reduced 3 with one expection
Yang, Weihua. "Supereulerian graphs, Hamiltonicity of graphes and several extremal problems in graphs." Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00877793.
Full textCarboni, Lucrezia. "Graphes pour l’exploration des réseaux de neurones artificiels et de la connectivité cérébrale humaine." Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALM060.
Full textThe main objective of this thesis is to explore brain and artificial neural network connectivity from agraph-based perspective. While structural and functional connectivity analysis has been extensivelystudied in the context of the human brain, there is a lack of a similar analysis framework in artificialsystems.To address this gap, this research focuses on two main axes.In the first axis, the main objective is to determine a healthy signature characterization of the humanbrain resting state functional connectivity. To achieve this objective, a novel framework is proposed,integrating traditional graph statistics and network reduction tools, to determine healthy connectivitypatterns. Hence, we build a graph pair-wise comparison and a classifier to identify pathological statesand rank associated perturbed brain regions. Additionally, the generalization and robustness of theproposed framework were investigated across multiple datasets and variations in data quality.The second research axis explores the benefits of brain-inspired connectivity exploration of artificialneural networks (ANNs) in the future perspective of more robust artificial systems development. Amajor robustness issue in ANN models is represented by catastrophic forgetting when the networkdramatically forgets previously learned tasks when adapting to new ones. Our work demonstrates thatgraph modeling offers a simple and elegant framework for investigating ANNs, comparing differentlearning strategies, and detecting deleterious behaviors such as catastrophic forgetting.Moreover, we explore the potential of leveraging graph-based insights to effectively mitigatecatastrophic forgetting, laying a foundation for future research and explorations in this area
Suprano, Ilaria. "Étude de la connectivité cérébrale par IRM fonctionnelle et de diffusion dans l’intelligence." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1282.
Full textThe idea that intelligence is embedded not only in specific brain regions, but also in efficient brain networks has grown up. Indeed, human brain organization is believed to rely on complex and dynamic networks in which the communication between cerebral regions guarantees an efficient transfer of information. These recent concepts have led us to explore the neural bases of intelligence using both advanced MRI techniques in combination with graph analysis. On one hand, advanced MRI techniques, such as resting-state functional MRI (rs-fMRI) and diffusion MRI (dMRI) allow the exploration of respectively the functional and the structural brain connectivity while on the other hand, graph theory models allow the characterization of brain networks properties at different scales, thanks to global and local metrics. The aim of this thesis is to characterize the topology of functional and structural brain networks in children and in adults with an intelligence quotient higher (HIQ) than standard levels (SIQ). First, we focused our attention on a children population with different cognitive characteristics. Two HIQ profiles, namely homogeneous (Hom-HIQ) and heterogeneous HIQ (Het-HIQ), have been defined based on clinical observations and Intelligence Quotient (IQ) sub-tests. Using resting-state fMRI techniques, we examined the functional network topology changes, estimating the "hub disruption index", in these two HIQ profiles. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to SIQ children, for the whole brain graph, for each hemispheric graph, and for the homotopic connectivity. These brain networks changes resulted to be more pronounced in Het-HIQ subgroup. Finally, we found significant correlations between the graph networks’ changes and the full-scale IQ, as well as some intelligence subscales. These results demonstrated for the first time, that different HIQ profiles are related to a different neural substrate organization. Then, the structural brain network connectivity, measured by dMRI in all HIQ children, were significantly different than in SIQ children. Also, we found strong correlations between the children brain networks density and their intelligence scores. Furthermore, several correlations were found between integration graph metrics suggesting that intelligence performances are probably related to a homogeneous network organization. These findings demonstrated that intelligence neural substrate is based on a strong white matter microarchitecture of the major fiber-bundles and a well-balanced network organization between local and global scales. This children population was finally studied using a memory-word task of fMRI. Significant changes were observed between both HIQ and SIQ groups. This study confirms our hypothesis that both HIQ profiles are characterized by a different brain activity, with stronger evidences in Het-HIQ children. Finally, we investigated both functional and structural connectivity in a population of adults HIQ. We found several correlations between graph metrics and intelligence sub-scores. As well as for the children population, high cognitive abilities of adults seem to be related brain structural and functional networks organization with a decreased modularity. In conclusion, the sensitivity of graph metrics based on advanced MRI techniques, such as rs-fMRI and dMRI, was demonstrated to be very helpful to provide a better characterization of children and adult HIQ, and further, to distinguish different intelligence profiles in children
Dai, Tianjiao. "Some vertex colouring problems and a generalisation of Hamilton-connectivity in graphs." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG067.
Full textThe decomposition of graphs refers to the process of breaking down a complex graph into simpler, smaller components, often with the goal of analysing or solving problems related to the graph. It is an important tool to display the global structure and properties in a more fine-grained manner, and also useful in solving problems that involve finding specific structures in a graph. There are several common types of graph decomposition techniques that are widely used in graph theory and related fields, including tree decomposition, block decomposition, modular decomposition, hierarchical decomposition, etc. This thesis studies two kinds of vertex decomposition of a graph: proper colourings (decomposition into independent sets) and Hamilton-connectivity (decomposition into internally-disjoint paths between two sets where the paths cover all the vertices of graphs)
Gargouri, Fatma. "Etude de la connectivité fonctionnelle dans les pathologies de mouvement de Parkinson et de Huntington en utilisant l’approche par graine et la théorie des graphes." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066487/document.
Full textFunctional magnetic resonance imaging (fMRI) is a technique that allows exploring neuronal activity using an endogenous contrast based on the oxygenation level of hemoglobin. This contrast is called BOLD (Blood oxygenated Level Dependent). It has been shown that fluctuations in the BOLD signal at rest, correlated in distant brain regions, defining long-distance brain functional networks. This is called functional connectivity. The latter represents the spontaneous activity of the brain and it is measured by fMRI at rest. Our research project has therefore combined a methodological aspect and two applications in the field of movement pathologies. In the first part of our project we studied data preprocessing strategies. The objective was to study the influence of the preprocessing steps and their order of application on the brain networks’ topology. We compared 12 different pretreatment strategies. In these strategies we applied the standard and most used techniques but with a different order of application. The following two studies used resting-state fMRI to study: Huntington's disease and Parkinson's disease. In these pathologies, we focused on the study of the brain networks addressed through the study of functional connectivity. We determined whether resting-state fMRI and graph theory measures were able to identify robust biomarkers of Huntington's disease progression in a longitudinal study. In the second study, we investigated the role of cholinergic basal nuclei of the forebrain and their connections in the onset of cognitive problems presented in Parkinson's disease. The seed-based analysis is a suitable method for this type of question
Oujamaa, Lydia. "Evolution topologique des hubs dans l'état de conscience altérée post-traumatique : un marqueur de récupération fonctionnelle." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALS013.
Full textThis work takes part in the field of translational research. Our aim was to explore thepost-lesional brain plasticity necessary to recover consciousness after a traumatic coma.The study of resting state functional connectivity, meaning the temporal correlation ofBOLD signal (blood oxygenation level dependent) between remote cerebral areas, wasapplied to severe traumatic brain injured (sTBI) patients.Using graph method, we explored the diagnosis and prognosis value of resting statefunctional connectivity during recovery of consciousness after a traumatic coma.Thirty six sTBI patients were studied in a cross sectional and a longitudinal design.We recorded a resting state functional MRI sequence while sTBI patients were eitherconscious or in altered state of consciousness when discharged from intensive care unit(ICU). A second fMRI was recorded after one month spent in a post-ICU rehabilitationunit.Our analysis focused on a hub disruption index (HDI) which expresses the reallocationof functional connections inside the graph. In the brain network, the hubs, which are definedas highly connected to the brain network in healthy subjects, have been characterizedwith integration, segregation and centrality metrics for information transfer.Our results suggest that the topological disruption of functional hubs is an objectivemapping of the brain network changes that correlates with post-TBI neurological recovery.Indeed, in our group analysis, the hub disruption index of the post TBI brainnetwork was sensitive to the state of consciousness and to its recovery during a onemonth follow-up. This index was also relevant to predict the level of disability 6 monthsafter injury.The computation of connectivity data in a metadata, the hub disruption index ofthe brain network, enhances the classical approach describing the post-traumatic brainplasticity as a loss and recovery of connectivity in one or several cortical networks. Therecovery of the brain network ability to compute local information in the functionalhubs could be necessary to recover consciousness after a traumatic coma. This resultis original as the recent litterature, based on the information integration theory andthe global workspace theory of consciousness, is considering severe TBI as a long rangeconnectivity disruption inducing a functional integration impairment.This pilot study was necessary prior to the assessment of the HDI on a single-subjectlevel and to quantifie the response of brain injured patients with disorder of consciousnessto several therapeutic options (psychostimulant drugs, electrical stimulation..)
König, Jean-Claude. "Les réseaux d'interconnexion et les algorithmes distribués." Paris 11, 1987. http://www.theses.fr/1987PA112069.
Full textThis thesis contains two parts. Ln the first one we study interconnection networks and in particular their fault tolerance. The first chapter deals with the extensions of networks. We construct networks with given connectivity and maximum degree by adding the vertices p by p. In such a way that the minimum number possible of links is deleted. Ln chapter 2 we study the vulnerability of bus networks; this leads us to study various notions of connectivity in uniform hypergraphs. The second part concerns distributed algorithms, in particular problems of broadcasting and routing. Chapter 3 deals with the problem of broadcasting information or requests in a distributed net work. We give a new algorithm to construct a spanning tree and apply it to the problem of mutual exclusion. We use methods of control knowledge transfers and also synchronization and filtering methods. Ln chapter 4 we present a "meta-algorithm" based on the notion of phases. Furthermore we specify the use and the importance of the network topology in the distributed computing. Ln these two chapters we determine the complexity in number or messages and time of the proposed algorithms. Finally we give in the appendix a scheduling algorithm for parallel computing which is optimal for the 2-sceps precedence graph (Gaussian elimination in dense matrices)
Cattai, Tiziana. "Leveraging brain connectivity networks to detect mental states during motor imagery." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS081.
Full textThe brain is a complex network and we know that inter-areal synchronization and de-synchronization mechanisms are crucial to perform motor and cognitive tasks. Nowadays, brain functional interactions are studied in brain-computer interface BCI) applications with more and more interest. This might have strong impact on BCI systems, typically based on univariate features which separately characterize brain regional activities. Indeed, brain connectivity features can be used to develop alternative BCIs in an effort to improve performance and to extend their real-life applicability. The ambition of this thesis is the investigation of brain functional connectivity networks during motor imagery (MI)-based BCI tasks. It aims to identify complex brain functioning, re-organization processes and time-varying dynamics, at both group and individual level. This thesis presents different developments that sequentially enrich an initially simple model in order to obtain a robust method for the study of functional connectivity networks. Experimental results on simulated and real EEG data recorded during BCI tasks prove that our proposed method well explains the variegate behaviour of brain EEG data. Specifically, it provides a characterization of brain functional mechanisms at group level, together with a measure of the separability of mental conditions at individual level. We also present a graph denoising procedure to filter data which simultaneously preserve the graph connectivity structure and enhance the signal-to-noise ratio. Since the use of a BCI system requires a dynamic interaction between user and machine, we finally propose a method to capture the evolution of time-varying data. In essence, this thesis presents a novel framework to grasp the complexity of graph functional connectivity during cognitive tasks
Termenon, Conde Maite. "Analyse par graphes de la connectivité fonctionnelle de repos par IRM : vers de nouveaux biomarqueurs de la récupération fonctionnelle dans l'AVC." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAS023/document.
Full textRoux, Marine. "Inférence de graphes par une procédure de test multiple avec application en Neuroimagerie." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT058/document.
Full textThis thesis is motivated by the analysis of the functional magnetic resonance imaging (fMRI). The need for methods to build such structures from fMRI data gives rise to exciting new challenges for mathematics. In this regards, the brain connectivity networks are modelized by a graph and we study some procedures that allow us to infer this graph.More precisely, we investigate the problem of the inference of the structure of an undirected graphical model by a multiple testing procedure. The structure induced by both the correlation and the partial correlation are considered. The statistical tests based on the latter are known to be highly dependent and we assume that they have an asymptotic Gaussian distribution. Within this framework, we study some multiple testing procedures that allow a control of false edges included in the inferred graph.First, we theoretically examine the False Discovery Rate (FDR) control of Benjamini and Hochberg’s procedure in Gaussian setting for non necessary positive dependent statistical tests. Then, we explore both the FDR and the Family Wise Error Rate (FWER) control in asymptotic Gaussian setting. We present some multiple testing procedures, well-suited for correlation (resp. partial correlation) tests, which provide an asymptotic control of the FWER. Furthermore, some first theoretical results regarding asymptotic FDR control are established.Second, the properties of the multiple testing procedures that asymptotically control the FWER are illustrated on a simulation study, for statistical tests based on correlation. We finally conclude with the extraction of cerebral connectivity networks on real data set
Faivre, Anthony. "Etude de la réorganisation de la connectivité cérébrale au repos dans la sclérose en plaques." Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM5022/document.
Full textResting-state fMRI (rs-fMRI) may provide important clue concerning disability in multiple sclerosis (MS) by exploring the spontaneous BOLD fluctuations at rest in the whole brain. The aim of this work is to depict the functional reorganization of resting-state networks in MS patients and to assess its potential relationships with disability.In the first part, we performed an fMRI protocol combining a rs-fMRI and task-associated fMRI during a motor task, in a group of early MS patients. This study evidenced a direct association between reorganization of connectivity at rest and during activation in the motor system of patients. In the second rs-fMRI study, we evidenced an increased of the global level of connectivity in most of the rs-networks, strongly associated with the level of disability of patients. In the third part, we evidenced in a 2-year longitudinal study using graph theoretical approach that MS patients exhibited a dynamical alteration of functional brain topology that significantly correlated with disability progression. In the last part, we evidenced that the transient clinical improvement following physical rehabilitation in MS patients is associated with reversible plasticity mechanisms located in the default mode network, the central executive network and in the left fronto-orbital cortex. These works evidence that MS patients exhibit a complex and dynamical functional reorganization of rs-networks, significantly associated with disability progression. This PhD thesis confirms that rs-fMRI is a relevant biomarker of pathophysiology leading to disability in MS and represents a promising tool for therapeutic assessment of MS patients in the future
Saive, Anne-Lise. "Les odeurs, une passerelle vers les souvenirs : caractérisation des processus cognitifs et des fondements neuronaux de la mémoire épisodique olfactive." Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10078/document.
Full textEpisodic memory is the memory that permits the conscious re-experience of specific personal events and associated with a specific context. This doctoral research aims at investigating the cognitive processes and the neural bases of episodic retrieval in humans. Odor-evoked memories are known to be more detailed and more emotional than memories triggered by other sensorial cues. These specificities explain why we studied odor-evoked memories. First, a novel behavioral task has been designed to study in a controlled way the memory of complex episodes comprising unfamiliar odors (What), localized spatially (Where), within a visual context (Which context). From this approach, we suggest that when the binding between the episodes’ dimensions is strong, the odor perception evokes the whole episodic memory. The episodic retrieval is mainly based on recollection processes, the feeling of knowing being insufficient to induce complete memory recovery. Moreover, emotion carried by odors, whatever its valence, promote accurate episodic retrieval. Functionally, episodic memory is underpinned by a distributed network, constituted of regions typically found in laboratory and autobiographical memory approaches. Accurate memories are associated with a specific neural network, from odor perception to memory re-experience. Modularity analyses show that neural interactions within this network also depend on memory accuracy. Altogether, results of this research suggest that episodic retrieval is a dynamic and complex process, triggered by odors perception, closely linked to other memory systems such as perceptual and semantic memories
Marrelec, Guillaume. "Méthodes bayésiennes pour l'analyse de la réponse hémodynamique et de la connectivité fonctionnelle en IRM fonctionnelle : apport à l'étude de la plasticité dans la chirurgie des gliomes de bas grade intracérébraux." Paris 11, 2003. http://www.theses.fr/2003PA112260.
Full textBOLD functional MRI (fMAI) is a recent imaging technique that can be used to dynamically and non-invasively study brain hemodynamic evolutions induced by neuronal activity. Use of fMRI could in particular allow for a better understanding of the plasticity phenomena that occur in the pathology of law-grade gliomas. To this end, development of new mathematical models is necessary. We first briefly introduce functional neuroimaging and the methodological framework of our work. We then develop our research on two complementary models, whose common goal is the study of brain plasticity. The first model considers the brain as a black box characterized by its response function, the so-called hemodynamic response. We proposed a robust Bayesian method to inter this response, through introduction of basic yet relevant a priori information about the underlying physiological process. This method was then generalized to account for most event-related fMRI acquisitions. A second model considers the interactions between regions involved in a given task. We developed a novel model, relying on the theory of independence graphs, that enables the quantification of interactions within this network. We also proposed a Bayesian procedure to estimate these quantities. We finally show that both approaches can be considered as two special cases within a more general model whose further development would allow for a better understanding of brain functional processes as measured by fMRI. Both methods developed were applied to clinical data to investigate brain plasticity observed among patients with law-grade brain gliomas. Most results obtained agree with the litterature. Some cast a new light on the functional reorganization that occurs among patients
Ait, Ali Kahina. "Modélisation et étude de performances dans les réseaux VANET." Phd thesis, Université de Technologie de Belfort-Montbeliard, 2012. http://tel.archives-ouvertes.fr/tel-00827552.
Full textGirardet, Xavier. "Paysage & [et] infrastructures de transport : modélisation des impacts des infrastructures sur les réseaux écologiques." Phd thesis, Université de Franche-Comté, 2013. http://tel.archives-ouvertes.fr/tel-01069242.
Full textObando, Forero Catalina. "Statistical graph models of temporal brain networks." Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS454.pdf.
Full textThe emerging area of complex networks has led to a paradigm shift in neuroscience. Connectomes estimated from neuroimaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) results in an abstract representation of the brain as a graph, which has allowed a major breakthrough in the understanding of topological and physiological properties of healthy brains in a compact and objective way. However, state of the art approaches often ignore the uncertainty and temporal nature of functional connectivity data. Most of the available methods in the literature have been developed to characterize functional brain networks as static graphs composed of nodes (brain regions) and links (FC intensity) by network metrics. As a consequence, complex networks theory has been mainly applied to cross-sectional studies referring to a single point in time and the resulting characterization ultimately represents an average across spatiotemporal neural phenomena. Here, we implemented statistical methods to model and simulate temporal brain networks. We used graph models that allow to simultaneously study how different network properties influence the emergent topology observed in functional connectivity brain networks. We successfully identified fundamental local connectivity mechanisms that govern properties of brain networks. We proposed a temporal adaptation of such fundamental connectivity mechanisms to model and simulate physiological brain network dynamic changes. Specifically, we exploited the temporal metrics to build informative temporal models of recovery of patients after stroke
Costa, Andrea. "Marine connectivity : exploring the role of currents and turbulent processes in driving it." Electronic Thesis or Diss., Aix-Marseille, 2017. http://www.theses.fr/2017AIXM0091.
Full textMarine connectivity is the transfer of larvae and/or individuals between distant marine habitats. Thanks to connectivity, distant marine population can face habitat pressure by relying on the transfer from distant populations of the same species. The transfer between distant populations in the ocean is made possible by the transport due to the currents. However, it is still not clear if the current field totally determines the persistence of the marine species or if the local demography plays a role. Crucially, in situ measurements of connectivity are extremely difficult. Therefore, our knowledge about connectivity is inferred from numerical dispersal simulations. The aim of this thesis is to clarify if we can deduce the persistence from the knowledge of the current field and to investigate the effect of numerical turbulence parameterizations in estimating connectivity. Firstly, I compare graph theory and metapopulation model to determine if currents have a predominant role. This allows to identify which graph theory measures reliably identifies reproductive sites important for persistence by relying on the knowledge of currents only. Secondly, I investigate the advantages and shortcomings of different turbulence closure models. This allows to clarify which TCS better reproduces turbulence activity in numerical models. Thirdly, I investigate generating mechanisms of bottom boundary turbulence. This allows to know the effective drag coefficient due to flow over rough topography and better estimate turbulent fluxes
Costa, Andrea. "Marine connectivity : exploring the role of currents and turbulent processes in driving it." Thesis, Aix-Marseille, 2017. http://www.theses.fr/2017AIXM0091/document.
Full textMarine connectivity is the transfer of larvae and/or individuals between distant marine habitats. Thanks to connectivity, distant marine population can face habitat pressure by relying on the transfer from distant populations of the same species. The transfer between distant populations in the ocean is made possible by the transport due to the currents. However, it is still not clear if the current field totally determines the persistence of the marine species or if the local demography plays a role. Crucially, in situ measurements of connectivity are extremely difficult. Therefore, our knowledge about connectivity is inferred from numerical dispersal simulations. The aim of this thesis is to clarify if we can deduce the persistence from the knowledge of the current field and to investigate the effect of numerical turbulence parameterizations in estimating connectivity. Firstly, I compare graph theory and metapopulation model to determine if currents have a predominant role. This allows to identify which graph theory measures reliably identifies reproductive sites important for persistence by relying on the knowledge of currents only. Secondly, I investigate the advantages and shortcomings of different turbulence closure models. This allows to clarify which TCS better reproduces turbulence activity in numerical models. Thirdly, I investigate generating mechanisms of bottom boundary turbulence. This allows to know the effective drag coefficient due to flow over rough topography and better estimate turbulent fluxes
Marie, Sylvain. "Déploiement optimal d’un réseau de capteurs sous des contraintes de couverture et de connectivité." Electronic Thesis or Diss., Paris, CNAM, 2019. http://www.theses.fr/2019CNAM1248.
Full textThe objectif of this thesis on wireless sensor networks is to study the deployment of a minimal number of sensors to cover specific targets instead of continuous areas. After a presentation of the characteristics of wireless sensor networks, and after justifying the interest of an optimal sensor deployment, we propose a graph-theory based model for wireless sensor networks. We then present a state of the art describing various mathematical programming models and resolution techniques regarding a number of optimization problems in such networks. We formulate several Mixed Integer Linear programs to solve the optimal sensor deployment problem under contraints related to the coverage of all targets and connectivity between sensors. Finally, we conceive a new heuristic for sensor placement when targets are placed in a square grid graph, and we conjecture that this heuristic returns an optimal solution in all cases
Frusque, Gaëtan. "Inférence et décomposition modale de réseaux dynamiques en neurosciences." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN080.
Full textDynamic graphs make it possible to understand the evolution of complex systems evolving over time. This type of graph has recently received considerable attention. However, there is no consensus on how to infer and study these graphs. In this thesis, we propose specific methods for dynamical graph analysis. A dynamical graph can be seen as a succession of complete graphs sharing the same nodes, but with the weights associated with each link changing over time. The proposed methods can have applications in neuroscience or in the study of social networks such as Twitter and Facebook for example. The issue of this thesis is epilepsy, one of the most common neurological diseases in the world affecting around 1% of the population.The first part concerns the inference of dynamical graph from neurophysiological signals. To assess the similarity between each pairs of signals, in order to make the graph, we use measures of functional connectivity. The comparison of these measurements is therefore of great interest to understand the characteristics of the resulting graphs. We then compare functional connectivity measurements involving the instantaneous phase and amplitude of the signals. We are particularly interested in a measure called Phase-Locking-Value (PLV) which quantifies the phase synchrony between two signals. We then propose, in order to infer robust and interpretable dynamic graphs, two new indexes that are conditioned and regularized PLV. The second part concerns tools for dynamical graphs decompositions. The objective is to propose a semi-automatic method in order to characterize the most important patterns in the pathological network from several seizures of the same patient. First, we consider seizures that have similar durations and temporal evolutions. In this case the data can be conveniently represented as a tensor. A specific tensor decomposition is then applied. Secondly, we consider seizures that have heterogeneous durations. Several strategies are proposed and compared. These are methods which, in addition to extracting the characteristic subgraphs common to all the seizures, make it possible to observe their temporal activation profiles specific to each seizures. Finally, the selected method is used for a clinical application. The obtained decompositions are compared to the visual interpretation of the clinician. As a whole, we found that activated subgraphs corresponded to brain regions involved during the course of the seizures and their time course were highly consistent with classical visual interpretation
Malagurski, Brigitta. "Signatures neurales de l'abolition et de la récupération de conscience à partir du coma." Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30039/document.
Full textThe aim of the present thesis was to characterize the functional and structural neural correlates of acute consciousness abolition induced by severe brain injury and identify early neural signatures of long-term neurological recovery. To do so, we studied brain-injured patients, recruited in the acute stage of coma, using resting-state functional and structural MRI. Our findings indicated a global topological brain reorganization in coma patients, reflected in dedifferentiated and less resilient high-order resting-state functional networks, paralleled with a loss of long-range fronto-parietal connections. On a regional level, we found a complex pattern of voxel-wise decrease and increase in functional connection density between the posteromedial cortex and the medial prefrontal cortex, regions previously described to have a critical role in conscious processing. These connection density patterns seemed to permit outcome prediction in patients, assessed three months post-coma. Furthermore, the multi-modal MRI analysis demonstrated a significant association between antero-posterior functional connectivity and structural integrity, providing further insights into the pathological underpinning of conscious processing
Tabchi, Theresia. "Relation entre enseignement et recherche dans le travail documentaire des enseignants-chercheurs – cas de l’enseignement de la théorie des graphes." Thesis, Reims, 2020. http://www.theses.fr/2020REIMS024.
Full textOur work deals with the teaching practices of university mathematics professors. These concur specificities: the articulation between teaching and research is an example. We seek to characterize the research impact in the teaching practices at university. We have chosen to explore this theme through the lens of the interaction with resources for teaching graph theory. The choice of graph theory is due to the fact that it is a branch of mathematics that belongs to "contemporary" mathematics, and that is taught in a wide spectrum of university majors in Lebanon as in France. Our methodology first draws on interviews with university professors. We rely on the documentational approach, in particular the concept of the scheme of use of resources to characterize the interactions of university professors with resources issued from teaching and research. We also analyze resources designed collectively by some of the university professors interviewed using the concept of connectivity, followed by observations of sessions by a university professor, one of the designers of the resources analyzed. We have shown that a comparison of the processes of the design of resources and their implementation in class allows us to characterize the various factors that impact the practices of university professors
Marie, Sylvain. "Déploiement optimal d’un réseau de capteurs sous des contraintes de couverture et de connectivité." Thesis, Paris, CNAM, 2019. http://www.theses.fr/2019CNAM1248/document.
Full textThe objectif of this thesis on wireless sensor networks is to study the deployment of a minimal number of sensors to cover specific targets instead of continuous areas. After a presentation of the characteristics of wireless sensor networks, and after justifying the interest of an optimal sensor deployment, we propose a graph-theory based model for wireless sensor networks. We then present a state of the art describing various mathematical programming models and resolution techniques regarding a number of optimization problems in such networks. We formulate several Mixed Integer Linear programs to solve the optimal sensor deployment problem under contraints related to the coverage of all targets and connectivity between sensors. Finally, we conceive a new heuristic for sensor placement when targets are placed in a square grid graph, and we conjecture that this heuristic returns an optimal solution in all cases
Darishchev, Alexander. "Analyse de connectivité et techniques de partitionnement de données appliquées à la caractérisation et la modélisation d'écoulement au sein des réservoirs très hétérogènes." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S162.
Full textComputer-based workflows have gained a paramount role in development and exploitation of natural hydrocarbon resources and other subsurface operations. One of the crucial problems of reservoir modelling and production forecasting is in pre-selecting appropriate models for quantifying uncertainty and robustly matching results of flow simulation to real field measurements and observations. This thesis addresses these and other related issues. We have explored a strategy to facilitate and speed up the adjustment of such numerical models to available field production data. Originally, the focus of this research was on conceptualising, developing and implementing fast proxy models related to the analysis of connectivity, as a physically meaningful property of the reservoir, with advanced cluster analysis techniques. The developed methodology includes also several original probability-oriented approaches towards the problems of sampling uncertainty and determining the sample size and the expected value of sample information. For targeting and prioritising relevant reservoir models, we aggregated geostatistical realisations into distinct classes with a generalised distance measure. Then, to improve the classification, we extended the silhouette-based graphical technique, called hereafter the "entire sequence of multiple silhouettes" in cluster analysis. This approach provided clear and comprehensive information about the intra- and inter-cluster dissimilarities, especially helpful in the case of weak, or even artificial, structures. Finally, the spatial separation and form-difference of clusters were graphically visualised and quantified with a scale-invariant probabilistic distance measure. The obtained relationships appeared to justify and validate the applicability of the proposed approaches to enhance the characterisation and modelling of flow. Reliable correlations were found between the shortest "injector-producer" pathways and water breakthrough times for different configurations of well placement, various heterogeneity levels and mobility ratios of fluids. The proposed graph-based connectivity proxies provided sufficiently accurate results and competitive performance at the meta-level. The use of them like precursors and ad hoc predictors is beneficial at the pre-processing stage of the workflow. Prior to history matching, a suitable and manageable number of appropriate reservoir models can be identified from the comparison of the available production data with the selected centrotype-models regarded as the class representatives, only for which the full fluid flow simulation is pre-requisite. The findings of this research work can easily be generalised and considered in a wider scope. Possible extensions, further improvements and implementation of them may also be expected in other fields of science and technology
Rannou, Léo. "Temporal Connectivity and Path Computation for Stream Graph." Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS418.
Full textFor a long time, structured data and temporal data have been analysed separately. Many real world complex networks have a temporal dimension, such as contacts between individuals or financial transactions. Graph theory provides a wide set of tools to model and analyze static connections between entities. Unfortunately, this approach does not take into account the temporal nature of interactions. Stream graph theory is a formalism to model highly dynamic networks in which nodes and/or links arrive and/or leave over time. The number of applications of stream graph theory has risen rapidly, along with the number of theoretical concepts and algorithms to compute them. Several theoretical concepts such as connected components and temporal paths in stream graphs were defined recently, but no algorithm was provided to compute them. Moreover, the algorithmic complexities of these problems are unknown, as well as the insight they may shed on real-world stream graphs of interest. In this thesis, we present several solutions to compute notions of connectivity and path concepts in stream graphs. We also present alternative representations - data structures designed to facilitate specific computations - of stream graphs. We provide implementations and experimentally compare our methods in a wide range of practical cases. We show that these concepts indeed give much insight on features of large-scale datasets. Straph, a python library, was developed in order to have a reliable library for manipulating, analysing and visualising stream graphs, to design algorithms and models, and to rapidly evaluate them
Nader, Noujoud. "Connectivity analysis of the EHG during pregnancy and labor." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2329.
Full textPreterm birth remains a major problem in obstetrics. Therefore, it has been a topic of interest for many researchers. Among the many methods used to record the uterine contractility, the most used is the abdominal EHG, as being an easy to use and a non-invasive tool. Many studies have reported that the use of this signal could be a very powerful tool to monitor pregnancy and to detect labor. It indeed permits to access the uterine as well as the synchronization of the uterine activity, by using multiple signals. It has been shown that the connectivity analysis gave promising results when using EHG recordings in clinical application, such as the classification labor/pregnancy contractions. However, in almost all previous studies EHG correlation matrices were often reduced keeping only their mean and standard deviations thus relevant information may have been missed due to this averaging, which may induce the relatively low classification rate reported so far. To characterize precisely the correlation matrix and quantify the associated connectivity, we proposed in this thesis to use a network measure technique based on graph theory. According to this approach, the obtained correlation matrix can be represented as graphs consisting of a set of nodes (electrodes) interconnected by edges (connectivity/correlation values between electrodes). The new framework, to analyze the EHG signals recorded during pregnancy and labor, is based on the characterization of the correlation between the uterine electrical activities and on its precise quantification by using graph theory approach. The processing pipeline includes i) the estimation of the statistical dependencies between the different recorded EHG signals, ii) the quantification of the obtained connectivity matrices using graph theory-based analysis and iii) the clinical use of network measures for pregnancy monitoring as well as for the classification between pregnancy and labor EHG bursts. A comparison with the already existing parameters used in the state of the art for labor detection and preterm labor prediction will also be performed. We also investigate a new method to study the EHG source connectivity, to overcome the problem of computing the connectivity at the abdominal surface level. The results of this thesis showed that this network-based approach is a very promising tool to quantify uterine synchronization, when applied at the abdominal level, for a better pregnancy monitoring. We expect this approach to be further used for the monitoring of pregnancy and would thus help for the early prediction of preterm labor
Durand, de Gevigney Olivier. "Orientations des graphes : structures et algorithmes." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM027/document.
Full textOrienting an undirected graph means replacing each edge by an arc with the same ends. We investigate the connectivity of the resulting directed graph. Orientations with arc-connectivity constraints are now deeply understood but very few results are known in terms of vertex-connectivity. Thomassen conjectured that sufficiently highly vertex-connected graphs have a k-vertex- connected orientation while Frank conjectured a characterization of the graphs admitting such an orientation. The results of this thesis are structures around the concepts of orientation, packing, connectivity and matroid. First, we disprove a conjecture of Recski on decomposing a graph into trees having orientations with specified indegrees. We also prove a new result on packing rooted arborescences with matroid constraints. This generalizes a fundamental result of Edmonds. Moreover, we show a new packing theorem for the bases of count matroids that induces an improvement of the only known result on Thomassen's conjecture. Secondly, we give a construction and an augmentation theorem for a family of graphs related to Frank's conjecture. To conclude, we disprove the conjecture of Frank and prove that, for every integer k >= 3, the problem of deciding whether a graph admits a k-vertex-orientation is NP-complete
Maceli, Peter Lawson. "Deciding st-connectivity in undirected graphs using logarithmic space." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1211753530.
Full textBader, El Dine Kamil. "Uterine synchronization analysis during pregnancy and labor using graph theory, classification based on machine learning." Thesis, Compiègne, 2022. http://www.theses.fr/2022COMP2680.
Full textThe overall objective of this thesis is to study the phenomenon of the propagation of uterine electrical activity by a approach based on graph theory. The first step in this thesis is to find new parameters extracted from the graphs which are suitable to represent the physio-pathological evolutions of the uterus. These parameters will be tested directly on th EHG signals recorded at the level of the abdomen then at the level of the sources identified from the EHGs. This analysis will be applied to the EHG signal i) globally (using the entire contraction) and ii) dynamically (using time windows in the contraction to characterize each time the corresponding graph). The second step will be to develop a new method based on neural networks and apply it on all the parameters already used in order to select the best parameters that can differentiate pregnancy and labor contractions. The expected results will be used both to enrich scientific knowledge in this field and to try to improve the performance of the prediction of prematurity in women
Hennayake, Kamal P. "Generalized edge connectivity in graphs." Morgantown, W. Va. : [West Virginia University Libraries], 1998. http://etd.wvu.edu/templates/showETD.cfm?recnum=383.
Full textTitle from document title page. Document formatted into pages; contains v, 87 p. : ill. Includes abstract. Includes bibliographical references (p. 64-72).
Sammarco, Matteo. "Dissémination multi-contenus opportuniste : monitorage passif et adaptation aux conditions du réseau." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066573/document.
Full textThe market penetration of mobile devices has experienced an impressive growth. Smartphones, tablets, and laptops have become both producers and consumers of user-generated contents. They also motivate novel communication paradigms such as the possibility to establish, in an opportunistic fashion, direct device-to-device links whenever two mobile nodes enter within the wireless range of each other. In this thesis, we consider the case of opportunistic dissemination of multiple large contents from an experimental point of view. This implies revisiting, among others, the common assumption that contacts have enough capacity to transfer any amount of data.In the first part of this thesis, we start from an Android implementation of EPICS, a network protocol designed for exchanging large contents in opportunistic networks, on off-the-shelf devices. After an deep analysis of application-level logs and captured wireless traces we found out limitations and uncovered improving possibilities. We then propose DAD, a new content dissemination protocol that adaptively sends bursts of data instead of the per-fragment transmission strategy of EPICS.The second part of this thesis deals with the scalability of legacy WLAN monitoring systems. We propose two original approaches. With the first one, based on trace similarity and community detection algorithms, we are able to identify how many monitor we need in a target area and where to place them. The second approach in based on collaborative measurements. In this case we face the risk of biased measures due attacks of malicious users generating adulterated traces. We then propose a method to detect such malicious behaviors
Gurung, Topraj. "Compact connectivity representation for triangle meshes." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47709.
Full textLimnios, Stratis. "Graph Degeneracy Studies for Advanced Learning Methods on Graphs and Theoretical Results Edge degeneracy: Algorithmic and structural results Degeneracy Hierarchy Generator and Efficient Connectivity Degeneracy Algorithm A Degeneracy Framework for Graph Similarity Hcore-Init: Neural Network Initialization based on Graph Degeneracy." Thesis, Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAX038.
Full textExtracting Meaningful substructures from graphs has always been a key part in graph studies. In machine learning frameworks, supervised or unsupervised, as well as in theoretical graph analysis, finding dense subgraphs and specific decompositions is primordial in many social and biological applications among many others.In this thesis we aim at studying graph degeneracy, starting from a theoretical point of view, and building upon our results to find the most suited decompositions for the tasks at hand.Hence the first part of the thesis we work on structural results in graphs with bounded edge admissibility, proving that such graphs can be reconstructed by aggregating graphs with almost-bounded-edge-degree. We also provide computational complexity guarantees for the different degeneracy decompositions, i.e. if they are NP-complete or polynomial, depending on the length of the paths on which the given degeneracy is defined.In the second part we unify the degeneracy and admissibility frameworks based on degree and connectivity. Within those frameworks we pick the most expressive, on the one hand, and computationally efficient on the other hand, namely the 1-edge-connectivity degeneracy, to experiment on standard degeneracy tasks, such as finding influential spreaders.Following the previous results that proved to perform poorly we go back to using the k-core but plugging it in a supervised framework, i.e. graph kernels. Thus providing a general framework named core-kernel, we use the k-core decomposition as a preprocessing step for the kernel and apply the latter on every subgraph obtained by the decomposition for comparison. We are able to achieve state-of-the-art performance on graph classification for a small computational cost trade-off.Finally we design a novel degree degeneracy framework for hypergraphs and simultaneously on bipartite graphs as they are hypergraphs incidence graph. This decomposition is then applied directly to pretrained neural network architectures as they induce bipartite graphs and use the coreness of the neurons to re-initialize the neural network weights. This framework not only outperforms state-of-the-art initialization techniques but is also applicable to any pair of layers convolutional and linear thus being applicable however needed to any type of architecture
Trakultraipruk, Somkiat. "Connectivity properties of some transformation graphs." Thesis, London School of Economics and Political Science (University of London), 2013. http://etheses.lse.ac.uk/624/.
Full textFraiman, Nicolás. "Connectivity of random graphs and networks." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119575.
Full textDans cette thèse, on étudie les propriétés de connexité pour plusieurs modèles de graphes aléatoires. Les résultats généralisent des théorèmes bien connus pour le modèle Erdös-Rényi et la percolation dans une boîte finie. On montre que pour les "Inhomogeneous Random Graphs" et les "Distance Fading Grid Networks", il y a un seuil pour la propriété de connexité et on trouve les valeurs des seuils correspondants. On caractérise aussi le diamètre pour le "Random Connection Model" quand l'espace est le tore de dimension d.
Bourgeois, Marc. "Impacts écologiques des formes d'urbanisation : modélisations urbaines et paysagères." Thesis, Besançon, 2015. http://www.theses.fr/2015BESA1029/document.
Full textThe global increase of urbanization during the past decades have induced a progressive artificialization of natural environments. The building of transport infrastructures and new housings causes a landscape fragmentation in an irreversible way and a strong decrease of the connectivity of ecological habitats. Maintaining the functionality of ecological networks is becoming a major goal of sustainable urban planning policies. With a special focus on urban evolutions in the horizon 2030 in the urban area of Besançon in eastern France (residential development and road traffic evolutions), this thesis aims to assess the potential impact of urban forms on landscape connectivity of animal species’ ecological networks. This research work promotes a modelling approach both on the field of theoretical and quantitative geography and landscape ecology.This approach follows three main steps: (1) simulating residential development and its associated road traffic changes using five prospective scenarios of differentiated urban forms; (2) modelling landscape graphs of various animal species using land-cover maps and ecological data; (3) assessing the potential impacts of each scenario on ecological networks from these graphs using connectivity metrics, with measures of the connectivity decrease attributable to each residential development scenario. Contrary to sprawled cities, the results show that compact and dense urban forms best promote the maintenance of ecological connectivity for the majority of species groups. Further analysis highlights the great contribution of road traffic evolutions regarding the ecological impacts of each scenario.According to some sensitivity analysis, the model used is quite robust. It demonstrates the interest of modelling in the decision-making process for environmental conservation and urban planning to think out the city of tomorrow in a sustainable way
Fortier, Quentin. "Aspects de la connexité avec contraintes de matroïdes dans les graphes." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAM059/document.
Full textThe notion of connectivity is fundamental in graph theory. We study thoroughly a recent development in this field, with the addition of matroid constraints.Firstly, we exhibit two reduction operations on connected graphs with matroid constraints. Using these operations, we generalize the Menger's theorem on connectivity and Edmond's theorem on packing of arborescences.However, this extension of Edmond's theorem does not ensure that the arborescences are spanning. It has been conjectured that one can always find such spanning arborescences. We prove this conjecture in some cases, including matroids of rank two and transversal matroids. We disprove this conjecture in the general case by providing a counter-example with more than 300 vertices, on a parallel extension of the Fano matroid.Finally, we explore other generalizations of connectivity with matroid constraints: in mixed graphs, hypergraphs and with reachability conditions
Zhang, Xiankun. "Generalizations of colorability and connectivity of graphs." Morgantown, W. Va. : [West Virginia University Libraries], 1998. http://etd.wvu.edu/templates/showETD.cfm?recnum=333.
Full textTitle from document title page. Document formatted into pages; contains vii, 97 p. : ill. Includes abstract. Includes bibliographical references (p. 93-96).
Vernet, Mathilde. "Modèles et algorithmes pour les graphes dynamiques." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMLH12.
Full textGraph problems have been widely studied in the case of static graphs. However, these graphs do not allow a time dimension to be considered, even though time is an important variable for the situations to model. Dynamic graphs make it possible to model evolution over time. This is a reason to wonder about graph problems in a dynamic context. First, it is necessary to define the most appropriate dynamic graphs model and the precise problem on those graphs. When the problem cannot be efficiently solved directly using known static graph methods, an algorithm specific to dynamic graphs must be designed and analyzed theoretically and practically.With that approach, this thesis' objective is to study graph problems' extensions to dynamic graphs. This works deals with several graph problems in a dynamic context by focusing on algorithmic aspects and without considering application domains
Neggaz, Mohammed Yessin. "Automatic classification of dynamic graphs." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0169/document.
Full textDynamic networks consist of entities making contact over time with one another. A major challenge in dynamic networks is to predict mobility patterns and decide whether the evolution of the topology satisfies requirements for the successof a given algorithm. The types of dynamics resulting from these networks are varied in scale and nature. For instance, some of these networks remain connected at all times; others are always disconnected but still offer some kind of connectivity over time and space (temporal connectivity); others are recurrently connected,periodic, etc. All of these contexts can be represented as dynamic graph classes corresponding to necessary or sufficient conditions for given distributed problems or algorithms. Given a dynamic graph, a natural question to ask is to which of the classes this graph belongs. In this work we provide a contribution to the automation of dynamic graphs classification. We provide strategies for testing membership of a dynamic graph to a given class and a generic framework to test properties in dynamic graphs. We also attempt to understand what can still be done in a context where no property on the graph is guaranteed through the distributed problem of maintaining a spanning forest in highly dynamic graphs
Tarabon, Simon. "La prise en compte des fonctionnalités écologiques dans l'aménagement des territoires et l'application de la séquence Éviter-Réduire-Compenser : De l'échelle projet à la planification Environmental impact assessment of development projects improved by merging species distribution and habitat connectivity modelling Integrating a landscape connectivity approach into mitigation hierarchy planning by anticipating urban dynamics. Landscape and Urban Planning Améliorer la prise en compte des fonctionnalités écologiques dans la séquence Éviter-Réduire-Compenser Maximizing habitat connectivity in the mitigation hierarchy. A case study on three terrestrial mammals in an urban environment The effects of climate warming and urbanised areas on the future distribution of Cortaderia selloana, pampas grass, in France." Thesis, Avignon, 2020. http://www.theses.fr/2020AVIG0720.
Full textOver the past decades, biodiversity erosion has speeded up and become a global environmental concern since. Anthropization has led to. The mitigation hierarchy (avoidance, reduction and offsetting of impacts) is a regulatory tool implemented in a context of habitat destruction and fragmentation, disrupting species’ life cycle. The objective is to achieve “no net loss” of biodiversity following urban development. Although biodiversity conservation regulations have recently better addressed ecosystem functioning, the mitigation hierarchy is still being implemented with little concern for the spatial configuration of ecosystems in the landscape. This thesis hypothesizes that the major difficulties encountered by stakeholders are, in part, methodological and technical. Situating our research at the knowledge-action interface, we propose a methodological framework based on several modeling approaches, to respond to the different scientific and operational challenges. This thesis joins forces with other scientific projects and stakeholders’ networks by exploring complementary axes. To this end, we first integrate spatio-temporal issues of biodiversity into overall mitigation hierarchy application, focusing on potential impacts and dimensioning at “territorial development project” scale through a case study on the new stadium in Lyon (Southern France). Combining species distributions models and spatial graphs improves habitat connectivity and therefore the design of the development projects. Next, we demonstrate the positive impacts on peri-urban habitat connectivity of pooling and anticipating offsets in the suburbs of Lyon. In the last part, we demonstrate the implications of an anticipated and planned approach to the mitigation hierarchy on a planning scale. We consider both ecological connectivity and urban dynamics, in an attempt to minimize the ecological impacts of urban sprawl by avoiding urbanization of areas of highest ecological value and then enhance the application of biodiversity offsetting. This method is tested on projections for the Toulouse conurbation (Southern France) by 2040. Thus, this thesis presents an overall approach that can help to increase habitat connectivity and to improve the design of territorial development projects at different spatial and temporal scales. This methodology is based on freeware available to all practitioners. It will serve planners, designers, and decision-makers needing to ensure that there are no significant or irreversible effects on biodiversity, and environmental authorities making sure that all environmental issues are taken into account in the design of development projects
Kartun-Giles, Alexander Paul. "Connectivity and centrality in dense random geometric graphs." Thesis, University of Bristol, 2017. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.720827.
Full textMalherbe, Caroline. "Imagerie des faisceaux de fibres et des réseaux fonctionnels du cerveau : application à l'étude du syndrome de Gilles de la Tourette." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00980572.
Full textSammarco, Matteo. "Dissémination multi-contenus opportuniste : monitorage passif et adaptation aux conditions du réseau." Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066573.
Full textThe market penetration of mobile devices has experienced an impressive growth. Smartphones, tablets, and laptops have become both producers and consumers of user-generated contents. They also motivate novel communication paradigms such as the possibility to establish, in an opportunistic fashion, direct device-to-device links whenever two mobile nodes enter within the wireless range of each other. In this thesis, we consider the case of opportunistic dissemination of multiple large contents from an experimental point of view. This implies revisiting, among others, the common assumption that contacts have enough capacity to transfer any amount of data.In the first part of this thesis, we start from an Android implementation of EPICS, a network protocol designed for exchanging large contents in opportunistic networks, on off-the-shelf devices. After an deep analysis of application-level logs and captured wireless traces we found out limitations and uncovered improving possibilities. We then propose DAD, a new content dissemination protocol that adaptively sends bursts of data instead of the per-fragment transmission strategy of EPICS.The second part of this thesis deals with the scalability of legacy WLAN monitoring systems. We propose two original approaches. With the first one, based on trace similarity and community detection algorithms, we are able to identify how many monitor we need in a target area and where to place them. The second approach in based on collaborative measurements. In this case we face the risk of biased measures due attacks of malicious users generating adulterated traces. We then propose a method to detect such malicious behaviors
Holtkamp, Andreas [Verfasser]. "Connectivity in graphs and digraphs : maximizing vertex-, edge- and arc-connectivity with an emphasis on local connectivity properties / Andreas Holtkamp." Aachen : Hochschulbibliothek der Rheinisch-Westfälischen Technischen Hochschule Aachen, 2013. http://d-nb.info/1038598796/34.
Full textBiyikoglu, Türker, and Josef Leydold. "Graphs of Given Order and Size and Minimum Algebraic Connectivity." WU Vienna University of Economics and Business, 2011. http://epub.wu.ac.at/3296/1/techreport%2D115.pdf.
Full textSeries: Research Report Series / Department of Statistics and Mathematics
Reinwardt, Manja. "Combinatorial and graph theoretical aspects of two-edge connected reliability." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2015. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-184297.
Full textAbazid, Majd. "Topological study of the brain functional organization at the early stages of Alzheimer's disease using electroencephalography." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS026.
Full textElectroencephalography (EEG) is still considered nowadays as a convenient neuroimaging technique in clinical applications, suitable for cognitively and physically disabled patients, as well as for serial tests. In fact, EEG is a non-invasive, cost-effective, and mobile technology. It is characterized by a high temporal resolution, which is crucial for the analysis of fast brain functional dynamics.There is a rich literature addressing the use of EEG to investigate brain activity alterations due to neurodegenerative diseases, especially Alzheimer's disease (AD). AD is a chronic neurodegenerative disease that leads to progressive decline of cognitive functions along with behavioral disorders and insidious loss of autonomy in daily living activities. We observe a growing interest in the earlier stages of the disease since curative treatments are still lacking. The preclinical stage of AD is asymptomatic, but the brain lesions due to AD are present. At this phase, the term of subjective cognitive impairment (SCI) has been recently defined. In the prodromal stage, mild cognitive impairment (MCI) patients show measurable memory impairments but their functional capacity is maintained. SCI and MCI patients are at high risk of developing AD.This thesis investigates the early diagnosis of AD at preclinical and prodromal stages using resting-state EEG, and addresses brain network analysis by studying the functional connectivity over several clinical stages of cognitive decline (SCI, MCI and Mild AD). To this end, we conduct a retrospective study using a clinical database that contains EEG signals recorded in real-life conditions.We first propose to exploit an entropy measure, termed “epoch-based entropy” (EpEn), as a measure of functional connectivity, that relies on a refined statistical modeling of EEG signals based on Hidden Markov Models. This measure characterizes the spatiotemporal changes in EEG signals by quantifying the information content of EEG signals, both at the time and spatial levels.Furthermore, we conduct a topological brain network analysis over the three stages of cognitive decline by employing the Graph Theory. The novelty of our work is twofold. Actually, this is the first work that: (i) addresses EEG brain network analysis over SCI, MCI and Mild AD stages simultaneously, and (ii) combines EpEn to Graph Theory since we have shown its effectiveness in quantifying the complete spatiotemporal alteration due to AD.In this thesis, we decided to invest the largest amount of EEG information for brain network analysis, by exploiting several frequency ranges (delta, theta, alpha, beta), several electrodes locations (instead of regions), and several network density scales (multiple graph thresholding). Therefore, another issue tackled in this thesis concerns the identification of relevant EEG markers to discriminate automatically between SCI, MCI and AD patients in the context of graph analysis framework. To this end, we propose an automatic hierarchical method for EEG analysis, which allows the extraction of relevant markers from large amount of information based on a single EEG connectivity measure.Finally, we also assess the correlation between the relevant EEG markers and the clinical markers at our disposal (MMSE, RL/RI-16, BREF)
Camby, Eglantine. "Connecting hitting sets and hitting paths in graphs." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209048.
Full textTout d’abord, nous considérons les deux problèmes suivants :le problème de vertex cover et celui de dominating set, deux cas particuliers du problème de hitting set. Un vertex cover est un ensemble de sommets qui rencontrent toutes les arêtes alors qu’un dominating set est un ensemble X de sommets tel que chaque sommet n’appartenant pas à X est adjacent à un sommet de X. La version connexe de ces problèmes demande que les sommets choisis forment un sous-graphe connexe. Pour les deux problèmes précédents, nous examinons le prix de la connexité, défini comme étant le rapport entre la taille minimum d’un ensemble répondant à la version connexe du problème et celle d’un ensemble du problème originel. Nous prouvons la difficulté du calcul du prix de la connexité d’un graphe. Cependant, lorsqu’on exige que le prix de la connexité d’un graphe ainsi que de tous ses sous-graphes induits soit borné par une constante fixée, la situation change complètement. En effet, pour les problèmes de vertex cover et de dominating set, nous avons pu caractériser ces classes de graphes pour de petites constantes.
Ensuite, nous caractérisons en termes de dominating sets connexes les graphes Pk- free, graphes n’ayant pas de sous-graphes induits isomorphes à un chemin sur k sommets. Beaucoup de problèmes sur les graphes sont étudiés lorsqu’ils sont restreints à cette classe de graphes. De plus, nous appliquons cette caractérisation à la 2-coloration dans les hypergraphes. Pour certains hypergraphes, nous prouvons que ce problème peut être résolu en temps polynomial.
Finalement, nous travaillons sur le problème de Pk-hitting set. Un Pk-hitting set est un ensemble de sommets qui rencontrent tous les chemins sur k sommets. Nous développons un algorithme d’approximation avec un facteur de performance de 3. Notre algorithme, basé sur la méthode primal-dual, fournit un Pk-hitting set dont la taille est au plus 3 fois la taille minimum d’un Pk-hitting set.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished