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Xu, Zhen. "On-surface synthesis of two-dimensional graphene nanoribbon networks". Kyoto University, 2020. http://hdl.handle.net/2433/254529.
Pełny tekst źródłaGarman, Paul Douglas. "Chemical Vapor Deposition of Silicon Oxycarbide Catalyzed Graphene Networks". The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523898208600691.
Pełny tekst źródłaRamli, Muhammad M. "Carbon nanotubes and graphene oxide networks for gas sensing". Thesis, University of Surrey, 2015. http://epubs.surrey.ac.uk/807845/.
Pełny tekst źródłaDe, Marco Martina. "Hierarchical carbon nanotube and graphene oxide networks for multifunctional applications". Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/47972.
Pełny tekst źródłaIqbal, Muhammad Zahir. "Structural and electrical characterization of doped graphene and carbon nanotube networks". Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/277570.
Pełny tekst źródłaEl grafè, considerat com una xarxa bidimensional d’àtoms de carboni units per enllaços híbrids sp2, és un tema de recerca molt prolífer en els últims anys, com a model de sòlid bidimensional, i molt particularment degut a les seves propietats electròniques, que poden tenir aplicacions interessants en dispositius electrònics, spintrònics o quàntics. La primera part de la Tesi descriu la modificació de les propietats estructurals i elèctriques del grafè utilitzant diferents mètodes per a dopar-lo: radiació ultraviolada d’alta energia (DUV) en atmosfera ambient, DUV en diferents gasos tals com oxigen o nitrogen, o irradiant amb un feix d’electrons (e-beam). Hem fabricat transistors d’efecte de camp (FET) amb grafè (exfoliat a partir del grafit, o bé obtingut per deposició química en fase vapor, CVD) utilitzant fotolitografia i e-beam litografia, i els hem caracteritzat mitjançant AFM, espectroscòpia Raman i mesures de transport elèctric, per a les que hem utilitzat la tècnica d’amplificació de baix soroll, el lock-in. Hem investigat com l’exposició a la llum ultraviolada en atmosfera ambient, modula les propietats elèctriques del grafè, de manera que la posició del punt de Dirac es desplaça cap a tensions de porta positives, cosa que implica dopatge de tipus-p, sense que hi hagi degradació de la mobilitat. El dopatge és estable al menys durant mesos. Amb el mateix mètode, quan només la meitat del dispositiu és exposat a la radiació ultraviolada mentre l’altre meitat és recobert per una màscara metàl·lica, hem obtingut una unió p-n. L’efecte de dopatge és més important i controlable, quan és fet en atmosfera d’oxigen. L’efecte més interessant que hem observat és la reversibilitat, quan el grafè dopat retorna al seu estat primitiu, en ser irradiat amb llum ultraviolada en atmosfera de nitrogen. També hem investigat el dopatge amb llum ultraviolada del grafè exfoliat mecànicament, de una, dues o tres capes, observant que es produeix sense una degradació significativa de la mobilitat dels portadors de càrrega. Posteriorment hem estudiat la deformació estructural del grafè quan és irradiat amb un feix d’electrons. Hem observat canvis estructurals en diferents etapes: el grafè evoluciona gradualment, a partir de la forma cristal·lina, cap a una fase d’estructura nanocristal·lina i finalment, després d’una certa dosi de irradiació, presenta una estructura amorfa. L’efecte d’ irradiar el grafè amb electrons actua com a dopant tipus-n, però en aquest cas la mobilitat decreix en incrementar la dosi, això implica que hi ha formació d’estats localitzats. La segona part de la Tesi tracta de capes primes de nanotubs de carboni, com a elèctrodes flexibles i transparents per a dispositius electrònics, en particular per aplicacions d’alta freqüència. Els resultats obtinguts mostren que, a baixes freqüències, la impedància augmenta en disminuir la densitat de nanotubs, tal com cal esperar. Tan la part real com la part imaginària de la impedància (mesurada fins a 20 GHz) decreixen abruptament en augmentar la freqüència més enllà de la freqüència de tall. La freqüència de tall no depèn únicament de la densitat de nanotubs en la capa, sinó també de la geometria de la mostra. El diagrama de Nyquist es pot interpretar amb un circuit equivalent consistent simplement en una resistència i un condensador en paral·lel. Els resultats experimentals s’ajusten bé a les simulacions fetes per espectroscòpia d’impedàncies (EIS). Els resultats posen en evidència que el comportament elèctric queda majoritàriament determinat per la resistència de contacte entre els nanotubs, que formen la xarxa amb una distribució totalment desordenada. Hem vist que capes primes de nanotubs de carboni conductores i flexibles, que poden ser també transparents, poden ser competitives en diferents aplicacions, com ara pantalles, cel·les solars fotovoltaiques o sensors selectius
MARTIN, JIMENEZ CRISTINA. "Nuovi materiali compositi basati su grafene". Doctoral thesis, Università degli Studi di Trieste, 2016. http://hdl.handle.net/11368/2908013.
Pełny tekst źródłaYarmolenko, O. V., S. A. Baskakov, Y. M. Shulga, P. I. Vengrus i O. N. Efimov. "Supercapacitors Based on Composite Polyaniline / Reduced Graphene Oxide with Network Nanocomposite Polymer Electrolyte". Thesis, Sumy State University, 2013. http://essuir.sumdu.edu.ua/handle/123456789/35510.
Pełny tekst źródłaBloess, Mark. "Harnessing Social Networks for Social Awareness via Mobile Face Recognition". Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/23792.
Pełny tekst źródłaEL, MERHIE AMIRA. "Single Layer Graphene Biointerface: Studying Neuronal Network Development and Monitoring Cell Behavior over Time". Doctoral thesis, Università degli studi di Genova, 2019. http://hdl.handle.net/11567/939896.
Pełny tekst źródłaRen, Haolin. "Visualizing media with interactive multiplex networks". Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0036/document.
Pełny tekst źródłaNowadays, information follows complex paths: information propagation involving on-line editors, 24-hour news providers and social medias following entangled paths acting on information content and perception. This thesis studies the adaptation of classical graph measurements to multiplex graphs, to build visualizations from several graphical representations of the networks, and to combine them (synchronized multi-view visualizations, hybrid representations, etc.). Emphasis is placed on the modes of interaction allowing to take in hand the multiplex nature (multilayer) of the networks. These representations and interactive manipulations are also based on the calculation of indicators specific to multiplex networks. The work is based on two main datasets: one is a 12-year archive of the Japanese public daily broadcast NHK News 7, from 2001 to 2013. Another lists the participants in the French TV/radio shows between 2010 and 2015. Two visualization systems based on a Web interface have been developed for multiplex network analysis, which we call "Visual Cloud" and "Laputa". In the Visual Cloud, we formally define a notion of similarity between concepts and groups of concepts that we call co-occurrence possibility (CP). According to this definition, we propose a hierarchical classification algorithm. We aggregate the layers in a multiplex network of documents, and integrate that hierarchy into an interactive word cloud. Here we improve the traditional word cloud layout algorithms so as to preserve the constraints on the concept hierarchy. The Laputa system is intended for the complex analysis of dense and multidimensional temporal networks. To do this, it associates a graph with a segmentation. The segmentation by communities, by attributes, or by time slices, forms views of this graph. In order to associate these views with the global whole, we use Sankey diagrams to reveal the evolution of the communities (diagrams that we have increased with a semantic zoom). This thesis allows us to browse three aspects of the most interesting aspects of the data miming and BigData applied to multimedia archives: The Volume since our archives are immense and reach orders of magnitude that are usually not practicable for the visualization; Velocity, because of the temporal nature of our data (by definition). The Variety that is a corollary of the richness of multimedia data and of all that one may wish to want to investigate. What we can retain from this thesis is that we met each of these three challenges by taking an answer in the form of a multiplex network analysis. These structures are always at the heart of our work, whether in the criteria for filtering edges using the Simmelian backbone algorithm, or in the superposition of time slices in the complex networks, or much more directly in the combinations of visual and textual semantic indices for which we extract hierarchies allowing our visualization
Zhou, Hang. "Graph algorithms : network inference and planar graph optimization". Thesis, Paris, Ecole normale supérieure, 2015. http://www.theses.fr/2015ENSU0016/document.
Pełny tekst źródłaThis thesis focuses on two topics of graph algorithms. The first topic is network inference. How efficiently can we find an unknown graph using shortest path queries between its vertices? We assume that the graph has bounded degree. In the reconstruction problem, the goal is to find the graph; and in the verification problem, the goal is to check whether a given graph is correct. We provide randomized algorithms based on a Voronoi cell decomposition. Next, we analyze greedy algorithms, and show that they are near-optimal. We also study the problems on special graph classes, prove lower bounds, and study the approximate reconstruction. The second topic is optimization in planar graphs. We study two problems. In the correlation clustering problem, the input is a weighted graph, where every edge has a label of h+i or h−i, indicating whether its endpoints are in the same category or in different categories. The goal is to find a partition of the vertices into categories that tries to respect the labels. In the two-edge-connected augmentation problem, the input is a weighted graph and a subset R of edges. The goal is to produce a minimum-weight subset S of edges, such that for every edge in R, its endpoints are two-edge-connected in the union of R and S. For planar graphs, we reduce correlation clustering to two-edge-connected augmentation, and show that both problems, although they are NP-hard, have a polynomial-time approximation scheme. We build on the brick decomposition technique developed recently
Yeliyur, Siddegowda Darshan. "Gray-cast iron classification based on graphite flakes using image morphology and neural networks". Thesis, California State University, Long Beach, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10017846.
Pełny tekst źródłaGray-cast iron is an iron carbon alloy which is regularly used in manufacturing processes. Carbon is distributed in the iron material in the form of graphite. The distribution of the graphite flakes in the alloy contributes greatly towards the chemical and physical properties of the metal alloy. Thus it is important to identify and classify the Gray-cast iron based on the morphological parameters of the graphite flakes. Gray-Cast iron is classified into five types in ISO-945 represented with the letters A through E. These five classes possess different structures or distributions of the graphite flakes. The current project presents an automated classification method using image processing and machine learning algorithms. The method presented here obtains the required parameters from the microstructure through image morphological operations. The image information is subsequently fed through a supervised machine learning algorithm which is trained using parameters such as area of the flakes, perimeter, minimum inter-particle distance and chord length from over twenty samples. The algorithm calculates the percentage of the type of the flakes present in the given image. The simulation is done in MATLAB and was tested for six images in each class. Class C and D were classified with 100 percent accuracy, Class A and B were classified with accuracy of 82 percent and Class E was identified with accuracy of 68 percent.
Celik, Numan. "Wireless graphene-based electrocardiogram (ECG) sensor including multiple physiological measurement system". Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15698.
Pełny tekst źródłaWan, William Bradley. "The synthesis of fused and derivatized dehydrobenzoannulenes and hexakis(phenylbutadiynyl)benzenes for elucidating the aromatic and NLO properties of the all-carbon network, graphdiyne /". view abstract or download file of text, 2001. http://wwwlib.umi.com/cr/uoregon/fullcit?p3018400.
Pełny tekst źródłaTypescript. Includes vita and abstract. Includes bibliographical references (leaves 237-258). Also available for download via the World Wide Web; free to University of Oregon users.
Friggeri, Adrien. "A Quantitative Theory of Social Cohesion". Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2012. http://tel.archives-ouvertes.fr/tel-00737199.
Pełny tekst źródłaKhames, Imene. "Nonlinear network wave equations : periodic solutions and graph characterizations". Thesis, Normandie, 2018. http://www.theses.fr/2018NORMIR04/document.
Pełny tekst źródłaIn this thesis, we study the discrete nonlinear wave equations in arbitrary finite networks. This is a general model, where the usual continuum Laplacian is replaced by the graph Laplacian. We consider such a wave equation with a cubic on-site nonlinearity which is the discrete φ4 model, describing a mechanical network of coupled nonlinear oscillators or an electrical network where the components are diodes or Josephson junctions. The linear graph wave equation is well understood in terms of normal modes, these are periodic solutions associated to the eigenvectors of the graph Laplacian. Our first goal is to investigate the continuation of normal modes in the nonlinear regime and the modes coupling in the presence of nonlinearity. By inspecting the normal modes of the graph Laplacian, we identify which ones can be extended into nonlinear periodic orbits. They are normal modes whose Laplacian eigenvectors are composed uniquely of {1}, {-1,+1} or {-1,0,+1}. We perform a systematic linear stability (Floquet) analysis of these orbits and show the modes coupling when the orbit is unstable. Then, we characterize all graphs for which there are eigenvectors of the graph Laplacian having all their components in {-1,+1} or {-1,0,+1}, using graph spectral theory. In the second part, we investigate periodic solutions that are spatially localized. Assuming a large amplitude localized initial condition on one node of the graph, we approximate its evolution by the Duffing equation. The rest of the network satisfies a linear system forced by the excited node. This approximation is validated by reducing the discrete φ4 equation to the graph nonlinear Schrödinger equation and by Fourier analysis. The results of this thesis relate nonlinear dynamics to graph spectral theory
Labarre, Anthony. "Combinatorial aspects of genome rearrangements and haplotype networks". Phd thesis, Universite Libre de Bruxelles, 2008. http://tel.archives-ouvertes.fr/tel-00482196.
Pełny tekst źródłaRuiz, Mathieu. "Codage cortical de la synesthésie graphème-couleur". Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENS020/document.
Pełny tekst źródłaSynesthesia is a fascinating phenomenon that offers the opportunity to study the neural bases of subjective experiences in healthy subjects. Grapheme-color synesthetes (1 to 5 % of the population – who do not know it most of the time) arbitrarily and systematically associate a specific color to letters or digits. This PhD thesis work focuses on this type of synesthesia and explores whether common neural networks are involved both in ‘real' color perception and synesthetic color experience. In a previous study from the host team using functional Magnetic Resonance Imaging (MRI), no implication of ‘color areas' where found (Hupé et al., 2012). A standard (univariate) statistical analysis of the data processing was used.This PhD thesis aims at determining if synesthetic colors involve real color neural networks with the use of a multivariate statistical technique (Multivoxel Pattern Analysis – MVPA). Unlike univariate analysis it uses sets of voxels (the pixels in 3D forming the images) and take into account their patterns of activation linked to the encoding of specific information in the brain. This encoding is performed at the neuronal level and fMRI indirectly and non-invasively quantifies it through hemodynamic variations induced by the neuronal activity. MVPA is a particularly adapted approach to measure fine grained and distributed information encoding. The goal of the thesis is to explore its efficiency for the study of grapheme-color synesthesia for which standard analyses failed. In practice, it requires the use of specific protocols, mastering numerous parameters influencing the results and the joint use of univariate analysis. In the first step of this thesis, we evaluated different methodological aspects to optimize the processing chain in order to obtain robust and reliable results.Then, we compared the neural processing of real colors and synesthetic colors in 2 groups of synesthetes (n=20) and non synesthetes (n=20). We found that synesthetic colors processing does not share common neural networks with real color processing. This suggests that the neural bases of synesthetic colors are not localized in the retinotopic visual areas or in the visual expertise areas (the ‘ventral pathway' areas). This may also suggest that, although those areas are involved, different neural networks are implicated in real color and synesthetic color perception. These results raise the question of the limits of the interpretation of the signal measured by fMRI, indirectly linked to the neuronal activity. The identification of the neural networks involved in the subjective experience of synesthetic colors remains an open issue
Samavat, Reza. "Mean Eigenvalue Counting Function Bound for Laplacians on Random Networks". Doctoral thesis, Universitätsbibliothek Chemnitz, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-159578.
Pełny tekst źródłaPasdeloup, Bastien. "Extending convolutional neural networks to irregular domains through graph inference". Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0048/document.
Pełny tekst źródłaThis manuscript sums up our work on extending convolutional neuralnetworks to irregular domains through graph inference. It consists of three main chapters, each giving the details of a part of a methodology allowing the definition of such networks to process signals evolving on graphs with unknown structures.First, graph inference from data is explored, in order to provide a graph modeling the support of the signals to classify. Second, translation operators that preserve neighborhood properties of the vertices are identified on the inferred graph. Third, these translations are used to shift a convolutional kernel on the graph in order to define a convolutional neural network that is adapted to the input data.We have illustrated our methodology on a dataset of images. While not using any particular knowledge on the signals, we have been able to infer a graph that is close to a grid. Translations on this graph resemble Euclidean translations. Therefore, this has allowed us to define an adapted convolutional neural network that is very close what one would obtain when using the information that signals are images. This network, trained on the initial data, has out performed state of the art methods by more than 13 points, while using a very simple and easily improvable architecture.The method we have introduced is a generalization of convolutional neural networks. As a matter of fact, they can be seen as aparticularization of our approach in the case where the graph is a grid. Our work thus opens the way to numerous perspectives, as it provides an efficient way to build networks that are adapted to the data
Leger, Jean-Benoist. "Modelling the topology of ecological bipartite networks with statistical models for heterogeneous random graphs". Paris 7, 2014. http://www.theses.fr/2014PA077185.
Pełny tekst źródłaAn ecological network is a representation of the whole set of interactions between species in a given context. Ecological scientists analyse the topological structure of such networks, in order to understand the underlying processes. The identification of sub-groups of highly-interacting species (usually called communities, or compartments) is an important stream of research. The most popular method for the search of communities in ecological networks is the modularity optimization method. However this popularity is more due to the first paper published on this topic than to a rational choice based on solid grounds. There are many other clustering methods that could be used to delimit communities in ecological networks. The analysis of complex networks is indeed a rapidly growing topic with many applications in several scientific fields. To our knowledge, no comparison of different clustering methods is available in the case of ecological networks. Here we reviewed the whole set of methods available for clustering networks and we compared them using an ecological benchmark. In order to assess the relative contribution of several processes to the network structure, we integrated exogenous information in the clustering model. We analysed two bipartite antagonistic networks with this method, a tree-fungus and tree-insect network. The results are still preliminary but the method seems to us very promising for future ecological studies. Finally we searched communities in a different kind of network, a mating network between individuals belonging to two hybridizing tree species. We used our results to discuss a concept which is central in ecology, the species concept
Peng, Han. "Spatial resolved electronic structure of low dimensional materials and data analysis". Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:2f3503eb-93bf-48d6-b6fb-13409b925748.
Pełny tekst źródłaRiediger, Steffen. "Implementierung eines Algorithmus zur Partitionierung von Graphen". Thesis, Universitätsbibliothek Chemnitz, 2007. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701098.
Pełny tekst źródłaEzzeddine, Diala. "A contribution to topological learning and its application in Social Networks". Thesis, Lyon 2, 2014. http://www.theses.fr/2014LYO22011/document.
Pełny tekst źródłaSupervised Learning is a popular field of Machine Learning that has made recent progress. In particular, many methods and procedures have been developed to solve the classification problem. Most classical methods in Supervised Learning use the density estimation of data to construct their classifiers.In this dissertation, we show that the topology of data can be a good alternative in constructing classifiers. We propose using topological graphs like Gabriel graphs (GG) and Relative Neighborhood Graphs (RNG) that can build the topology of data based on its neighborhood structure. To apply this concept, we create a new method called Random Neighborhood Classification (RNC).In this method, we use topological graphs to construct classifiers and then apply Ensemble Methods (EM) to get all relevant information from the data. EM is well known in Machine Learning, generates many classifiers from data and then aggregates these classifiers into one. Aggregate classifiers have been shown to be very efficient in many studies, because it leverages relevant and effective information from each generated classifier. We first compare RNC to other known classification methods using data from the UCI Irvine repository. We find that RNC works very well compared to very efficient methods such as Random Forests and Support Vector Machines. Most of the time, it ranks in the top three methods in efficiency. This result has encouraged us to study the efficiency of RNC on real data like tweets. Twitter, a microblogging Social Network, is especially useful to mine opinion on current affairs and topics that span the range of human interest, including politics. Mining political opinion from Twitter poses peculiar challenges such as the versatility of the authors when they express their political view, that motivate this study. We define a new attribute, called couple, that will be very helpful in the process to study the tweets opinion. A couple is an author that talk about a politician. We propose a new procedure that focuses on identifying the opinion on tweet using couples. We think that focusing on the couples's opinion expressed by several tweets can overcome the problems of analysing each single tweet. This approach can be useful to avoid the versatility, language ambiguity and many other artifacts that are easy to understand for a human being but not automatically for a machine.We use classical Machine Learning techniques like KNN, Random Forests (RF) and also our method RNC. We proceed in two steps : First, we build a reference set of classified couples using Naive Bayes. We also apply a second alternative method to Naive method, sampling plan procedure, to compare and evaluate the results of Naive method. Second, we evaluate the performance of this approach using proximity measures in order to use RNC, RF and KNN. The expirements used are based on real data of tweets from the French presidential election in 2012. The results show that this approach works well and that RNC performs very good in order to classify opinion in tweets.Topological Learning seems to be very intersting field to study, in particular to address the classification problem. Many concepts to get informations from topological graphs need to analyse like the ones described by Aupetit, M. in his work (2005). Our work show that Topological Learning can be an effective way to perform classification problem
MacGill, Ross. "Fast moving neutrons, graphite moderators and radioactive clouds : an ANT account of the Chernobyl accident's risky network". Thesis, University of Glasgow, 2017. http://theses.gla.ac.uk/8260/.
Pełny tekst źródłaWychowaniec, Jacek. "Designing nanostructured peptide hydrogels containing graphene oxide and its derivatives for tissue engineering and biomedical applications". Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/designing-nanostructured-peptide-hydrogels-containing-graphene-oxide-and-its-derivatives-for-tissue-engineering-and-biomedical-applications(409e60a2-ed17-45bf-ab6c-b76ede937a67).html.
Pełny tekst źródłaKormoš, Lukáš. "2D molekulární systémy na površích". Doctoral thesis, Vysoké učení technické v Brně. CEITEC VUT, 2021. http://www.nusl.cz/ntk/nusl-438774.
Pełny tekst źródłaDEL, PUPPO SIMONE. "MATERIALI 2D SU SUPERFICI METALLICHE: UN APPROCCIO NUMERICO". Doctoral thesis, Università degli Studi di Trieste, 2023. https://hdl.handle.net/11368/3041020.
Pełny tekst źródłaAlthough the extensive work on 2D materials, a comprehensive understanding of the layer-substrate interaction and how this affects the structure and the electronic properties is still lacking.With the aim of shedding light on this still open issue, in this work we extensively investigated through numerical simulations some selected systems based on two different 2D materials, Graphene (G) on Nickel (Ni) substrates (most of the work) and Blue-Phosphorus (BP) on Gold (Au) substrate, using different and, to some extent, complementary numerical approaches. Most of the work consisted in quantum mechanical ab-initio simulations based on Density Functional Theory (DFT), paying attention to some specific technical details to ensure the accuracy and the reliability of the results. Part of the work concerned the construction via neural network techniques and the validation of new interatomic potentials to extend the investigation of G/Ni systems to more realistic configurations or to dynamical processes not directly affordable by ab-initio calculations. Throughout the work, a direct comparison with published or new experimental results is discussed. Graphene can be easily grown by CVD on nickel substrates but its electronic and structural properties depend on the matching/mismatching and on the alignment/misalignment between its hexagonal lattice and the underlying surface lattice.The thesis starts with the investigation of epitaxial G on Ni(111), which is already very well known.Starting from a set of DFT calculations that we also used as a benchmark to refine many technical details of our simulations on other new configurations, we used a Neural Network to generate an interatomic potential able to accurately predict energy and forces in this system. The new potential allows to perform molecular dynamics simulations with thousands of atoms with accuracy close to that of DFT, paving the way for large-scale simulations of such system. We report a successful application on large G domains showing cohexistence of different registries with the substrate.After that, structural reconstruction that Ni(111) surface undergoes at high temperatures during CVD process has been investigated. We showed how the presence of rotated domains of graphene with respect to Ni(111) lattice affects the formation of a nickel carbide phase, Ni2C,underneath. Furthermore, we studied the intercalation of Carbon Monoxide under epitaxial G grown on Ni(111) providing a systematic investigation of the intercalated CO pattern, highlighting the modifications induced on the graphene electronic structure.The most important signature of CO intercalation is a shift of Dirac cones linearly dependent on the CO coverage, opening the way to application as gas sensor to easily detect and quantify its presence. In this work, G on Ni(100)has also been studied. Such an interface, due to lattice mismatch, presents a stripe moiré pattern in which strongly (chemisorbed) and weakly (physisorbed) interacting G regions with Ni surface alternate, inducing anisotropic modulated electronic structure and reactivity properties.Here we provided a full investigation of different kind of defects of G layer and we investigated how they can increase the reactivity of graphene for metal adatoms or molecules adsorption. The last part of the thesis has been devoted to Blue-Phosphorus,a new 2D material made by only P atoms arranged similarly to graphene but with a larger lattice parameter and a small buckling of the two constituent sublattices.To describe BP grown on Au(111),we identified as the best candidate a structural model formed by P9 pyramidal shaped domains connected by Au adatoms in a 5x5 supercell.The nice correspondence with experimental STM images and ARPES spectra, allows to discriminate among different possible models,indicating once again the necessity of a synergetic effort between simulations and experiments to shed light on the structure and properties of real systems.
Moscu, Mircea. "Inférence distribuée de topologie de graphe à partir de flots de données". Thesis, Université Côte d'Azur, 2020. http://www.theses.fr/2020COAZ4081.
Pełny tekst źródłaThe second decade of the current millennium can be summarized in one short phrase: the advent of data. There has been a surge in the number of data sources: from audio-video streaming, social networks and the Internet of Things, to smartwatches, industrial equipment and personal vehicles, just to name a few. More often than not, these sources form networks in order to exchange information. As a direct consequence, the field of Graph Signal Processing has been thriving and evolving. Its aim: process and make sense of all the surrounding data deluge.In this context, the main goal of this thesis is developing methods and algorithms capable of using data streams, in a distributed fashion, in order to infer the underlying networks that link these streams. Then, these estimated network topologies can be used with tools developed for Graph Signal Processing in order to process and analyze data supported by graphs. After a brief introduction followed by motivating examples, we first develop and propose an online, distributed and adaptive algorithm for graph topology inference for data streams which are linearly dependent. An analysis of the method ensues, in order to establish relations between performance and the input parameters of the algorithm. We then run a set of experiments in order to validate the analysis, as well as compare its performance with that of another proposed method of the literature.The next contribution is in the shape of an algorithm endowed with the same online, distributed and adaptive capacities, but adapted to inferring links between data that interact non-linearly. As such, we propose a simple yet effective additive model which makes use of the reproducing kernel machinery in order to model said nonlinearities. The results if its analysis are convincing, while experiments ran on biomedical data yield estimated networks which exhibit behavior predicted by medical literature.Finally, a third algorithm proposition is made, which aims to improve the nonlinear model by allowing it to escape the constraints induced by additivity. As such, the newly proposed model is as general as possible, and makes use of a natural and intuitive manner of imposing link sparsity, based on the concept of partial derivatives. We analyze this proposed algorithm as well, in order to establish stability conditions and relations between its parameters and its performance. A set of experiments are ran, showcasing how the general model is able to better capture nonlinear links in the data, while the estimated networks behave coherently with previous estimates
Renoust, Benjamin. "Analysis and Visualisation of Edge Entanglement in Multiplex Networks". Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00942358.
Pełny tekst źródłaTurco, Antonio. "Use of carbon nanotubes for novel approaches towards spinal network repairing". Doctoral thesis, Università degli studi di Trieste, 2013. http://hdl.handle.net/10077/8663.
Pełny tekst źródłaNanotechnology underwent a very rapid development in the last decades, thanks to the invention of different techniques that allow reaching the nanoscale. The great interest in this area arises from the variety of possible applications in different fields, such as electronics, where the miniaturization of components is a key factor, but also medicine. The creation of smart systems able to carry out a specific task in the body in a controlled way, either in diagnosis or therapy or tissue engineering, is the ultimate goal of a newborn area of research, called nanomedicine. In fact, to reach such an outstanding objective, a nanometer‐sized material is needed and carbon nanotubes (CNTs) are among the most promising candidates. The aim of this thesis was to study this opportunity and, in particular, the possible application of carbon nanotubes for spinal network repairing. After a review of the main features of neuronal network systems and the most common techniques to study their functionality, possible applications of nanotechnology for nanomedicine purposes are considered, focusing the attention on CNTs as neuronal interface in nerve tissue engineering. The work can be divided into two big parts. In the first part the impact of carbon nanotubes on various neuronal systems was studied. Different form of carbonaceous materials (carbon nanotubes, nanohorns and graphene) were deposited in a homogeneous way on a glass surface playing with organic functionalization and different deposition techniques. Hippocampal neuronal cells were grown on their surface to better understand how morphology and conductivity of the material could influence the activity of the neuronal network evidencing how both these characteristics could affect the electrophysiological properties of neurons. Then, also spinal neurons were grown on carbon nanotubes network deposited on a glass substrate to evaluate, for the first time, the impact of carbon nanotubes on this kind of cells. The tight interaction between these two materials appeared to cause a faster maturation of the spinal neurons with respect II to the control grown on a glass substrate. The long-term impact on a complex tissue (spinal cord slice) grown on carbon nanotubes carpet was also studied. The intimate interaction between the two materials observed by TEM and SEM analysis caused an increase in dimensions and number of neuronal fibers that comes out from the body of a spinal cord slice. An increase in electrophysiological activity of all neuronal network of the slice was also reported. In the second part of the work different conductive biocompatible nanocomposite materials based on carbon nanotubes and “artificial” polymers (such as Nafion, PVA, PET, PEI, PDMS and PANI) were investigated. The idea is to test these materials as neuronal prosthesis to repair spinal cord damage. All the prepared scaffolds showed CNTs on the surface favoring CNTs-neurons interaction. To address this aim different techniques and different organic functionalizations of CNTs were utilized to control supramolecular interactions between the nanomaterial and polymers orienting the deposition of the CNTs and preventing their aggregation. After that, an innovative method to study the possible ability of this nanocomposite materials to transmit a neuronal signal between two portions of spinal cord was designed. Functionalization of gold surfaces with thiolated carbon nanotubes have been conducted in order to develop suitable devices for neuronal stimulation and consequent spinal cord lesions repairing. In particular thiol groups were introduced on the graphitic surface of carbon nanotubes by means of covalent functionalization. First of all, the interaction of CNTs with gold nanoparticles has been evaluated, then a gold surface has been coated by means of contact printing technique with a homogeneous film of CNTs. This hybrid material could be useful to produce innovative electrodes for neuronal stimulation
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Combe, David. "Détection de communautés dans les réseaux d'information utilisant liens et attributs". Phd thesis, Université Jean Monnet - Saint-Etienne, 2013. http://tel.archives-ouvertes.fr/tel-01056985.
Pełny tekst źródłaBOSCHI, Alex. "Studio dei meccanismi di trasporto di carica in film sottili a base di materiali correlati al grafene (GRM)". Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2021. http://hdl.handle.net/11380/1244690.
Pełny tekst źródłaThe development of cheap techniques to produce large sheets of monoatomic thick materials, such as graphene [1], opened new avenues to design nanostructured materials with pre-programmed chemical and physical properties. Most of the technologically relevant graphene-related materials (GRMs) systems are networks composed of randomly distributed and highly defective 2D microsheets [2]. While the charge transport has been extensively studied in single nanosheets [3], a comprehensive study that correlates the electrical properties of networks composed of purely 2D graphene-based materials with the complexity of the material structure and morphology is still missing. The aim of this work is to investigate charge transport (CT) in GRMs films, going towards structures with increasing disorder. In particular we investigated the CT mechanisms occurring at the sheet-to-sheet interface – typically the interfacial mechanisms are considered as bottlenecks – as well as the role of the geometrical complexity of the network in the overall electrical conductivity of the nanosheets assemblies. As prototypical 2D material we used single monolayer sheets of graphene oxide (GO), which consists of a conductive graphene lattice including oxygen functionalities/ defects both on the basal plane and at the edges of the sheet. Electrical insulating GO sheets are deposited on silicon oxide substrates and thermally reduced restoring partially the conductive properties of the 2D sheets. In addition to reduced GO, we employed a GRM made of multiple staked sheets of (partially oxidised) graphene bilayers: electrochemical exfoliated GO (eGO) [4].We exploited different deposition methods: i) spin-coating, ii) spray-coating and iii) vacuum-assisted filtration to fabricate macroscopic GRMs thin films with sheets partially stacked. Chemical and morphological properties of the films were characterized by X-ray Photoelectron Spectroscopy (XPS), Atomic Force Microscopy (AFM) and X-ray Diffraction (XRD) measurements. We investigated transport mechanisms measuring the temperature-dependence of the electrical resistivity (ρ) from room temperature down to 5 K. Possible ambiguities on the quantitative analysis of ρ(T) were solved by using a robust self-consistent method based on the reduced activation energy [5], i.e. the logarithmic derivative of resistivity versus temperature: W(T)=-(d lnρ)⁄(d lnT ). This mathematical transformation allowed to analyse ρ(T) dataset with linear functions. We correlated the transport characteristic parameters with the degree of order of our samples and elucidate the role of the sheets vertical stacking, that is of the π-π interaction between overlapped aromatic clusters, in the CT in the film. We also highlighted the differences in CT between reduced GO based films and eGO ones. The presented work could pave the way to develop new models and protocols to access the CT mechanisms in realistic GRMs, such as inks and polymer composites. [1] Ferrari, A. C. et al. Nanoscale 7, 4598-4810, (2015). [2] Palermo V., Chem. Comm. 49, 28, 2848-2857 (2013); Kelly A. et al, Science 356, 6333 (2017). [3] Eda G. et al, J. Physics. Chem.C 113, 15768 (2009); Kaiser a. et al, Nano Letters 9, 1787 (2009); Joung D. and Khondaker S., Phys. Rev. B 86, 235423 (2012). [4] Xia Z. et al, J. Physics. Chem.C 123, 15122 (2019). [5] Zabrodskii A. G., Philos. Mag. B 81, 1131 (2001).
Wauquier, Pauline. "Task driven representation learning". Thesis, Lille 3, 2017. http://www.theses.fr/2017LIL30005/document.
Pełny tekst źródłaMachine learning proposes numerous algorithms to solve the different tasks that can be extracted from real world prediction problems. To solve the different concerned tasks, most Machine learning algorithms somehow rely on relationships between instances. Pairwise instances relationships can be obtained by computing a distance between the vectorial representations of the instances. Considering the available vectorial representation of the data, none of the commonly used distances is ensured to be representative of the task that aims at being solved. In this work, we investigate the gain of tuning the vectorial representation of the data to the distance to more optimally solve the task. We more particularly focus on an existing graph-based algorithm for classification task. An algorithm to learn a mapping of the data in a representation space which allows an optimal graph-based classification is first introduced. By projecting the data in a representation space in which the predefined distance is representative of the task, we aim at outperforming the initial vectorial representation of the data when solving the task. A theoretical analysis of the introduced algorithm is performed to define the conditions ensuring an optimal classification. A set of empirical experiments allows us to evaluate the gain of the introduced approach and to temper the theoretical analysis
Schiller, Benjamin. "Graph-based Analysis of Dynamic Systems". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-230611.
Pełny tekst źródłaVieira, Milreu Paulo. "Enumerating functional substructures of genome-scale metabolic networks : stories, precursors and organisations". Phd thesis, Université Claude Bernard - Lyon I, 2012. http://tel.archives-ouvertes.fr/tel-00850704.
Pełny tekst źródłaTosatto, Silvia. "A teledetection system based on surface plasmon resonance sensors for environmental pollutants". Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3422980.
Pełny tekst źródłaI sensori basati sulla plasmonica di superficie (SPR) sono rifrattometri, basati sulla fisica dei film sottili, che misurano le variazioni di indice di rifrazione che avvengono sulla superficie di uno strato metallico supportante un plasmone di superficie (Homola , 2008). L’ attività di ricerca si è sviluppata come uno studio ed implementazione di sensori SPR innovativi e delle loro possibili applicazioni, in particolare per la rilevazione di sostanze inquinanti. Sono stati simulati in ambiente Matlab sensori SPR innovativi, comprendenti materiali peculiari. Tali sensori comprendono in particolare metalli mostranti una Risonanza Plasmonica Invertita (ISPR), oltre che un singolo strato di Graphene (SGL). Un articolo è stato sottomesso su tali studi. Sono stati inoltre implementati in laboratorio vari prototipi di sensori basati sulla plasmonica di superficie. Innanzi tutto sono state effettuate delle misure di riflettività con i gas elio e pentano mediante un sensore basato sulla plasmonica di superficie e con un setup dinamico, quindi è stato creato un nuovo sensore utilizzante un un sistema ottico di tipo statico ed un prisma cilindrico ad alto indice di rifrazione, migliorando il più possibile la qualità del fascio ottico e filtrandolo opportunamente. Altresì è stato innovativamente utilizzato nel setup ottico uno specchio deformabile, in grado di correggere le aberrazioni ottiche presenti nello stesso. Oltre a ciò sono stati individuati i possibili elementi di una rete wireless di sensori SPR progettata per il monitoraggio ambientale, i dati ottenibili da un sensore SPR, una strategia per la diffusione dei dati ed una stima dei consumi energetici. Infine sono stati implementati in laboratorio due diversi setup di prova per una piccola rete wireless di sensori, formata da due sensori SPR controllati da un computer o da un microcontrollore, antenne ZigBee e da un computer principale per la ricezione, analisi e diffusione in Internet dei dati. L’ attività di ricerca presentata in questa tesi ha quindi dimostrato la possibilità della creazione di una rete wireless di sensori basati sulla Plasmonica di Superficie e con accesso Internet a banda larga, finalizzata alla rilevazione di sostanze inquinanti in ambiente acquoso, e due piccole versioni di prova della stessa sono state implementate in laboratorio.
Candell, Richard. "Performance Estimation, Testing, and Control of Cyber-Physical Systems Employing Non-ideal Communications Networks". Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCK017.
Pełny tekst źródłaWireless technology is a key enabler of the promises of Industry 4.0 (Smart Manufacturing). As such, wireless technology will be adopted as a principal mode of communication within the factory beginning with the factory enterprise and eventually being adopted for use within the factory workcell. Factory workcell communication has particular requirements on latency, reliability, scale, and security that must first be met by the wireless communication technology used. Wireless is considered a non-ideal form of communication in that when compared to its wired counterparts, it is considered less reliable (lossy) and less secure. These possible impairments lead to delay and loss of data in industrial automation system where determinism, security, and safety is considered paramount. This thesis investigates the wireless requirements of the factory workcell and applicability of existing wireless technology, it presents a modeling approach to discovery of architecture and data flows using SysML, it provides a method for the use of graph databases to the organization and analysis of performance data collected from a testbed environment, and finally provides an approach to using machine learning in the evaluation of cyberphysical system performance
Tackx, Raphaël. "Analyse de la structure communautaire des réseaux bipartis". Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS550.pdf.
Pełny tekst źródłaIn the real world, numerous networks appear naturally, they are everywhere, in many disciplines, for example in computer science with router networks, satellite networks, webpage networks, in biology with neural networks, in ecology with biological interaction networks, in linguistic with synonym networks, in law with legal decision networks, in economy with interbank networks, in social sciences and humanities with social networks. Generally, a network reflects the interactions between many entities of a system. These interactions have different sources, a social link or a friendship link in a social network, a cable in a router network, a chemical reaction in a protein-protein interaction network, a hyperlink in a webpage network. Furthermore, the rapid democratization of digital technology in our societies, with internet in particular, leads to create new systems which can be seen as networks. Finally, all these networks depict very specific features : they come from pratical contexts, most of the time they are big (they may be comprised of several billion of nodes and links, containing a large amount of information), they share statistical properties. In this regard, they are called real-world networks or complex networks. Nowaday, network science is a research area in its own right focusing on describing and modeling these networks in order to reveal their main features and improve our understanding of their mecanisms. Most of the works in this area use graphs formalism which provides a set of mathematical tools well suited for analyzing the topology of these networks. It exists many applications, for instance applications in spread of epidemy or computer viruses, weakness of networks in case of a breakdown, attack resilience, study for link prediction, recommandation, etc. One of the major issue is the identification of community structure. The large majority of real-world networks depicts several levels of organization in their structure. Because of there is a weak global density coupled with a strong local density, we observe that nodes are usually organized into groups, called communities, which are more internally connected than they are to the rest of the network. Moreover, these structures have a meaning in the network itself, for example communities of a social network may correspond to social groups (friends, families, etc.), communities of a protein-protein network may translate fonctions of a cell, communities may be also related to similar subjects in a webpage network [...]
Costes, Benoît. "Vers la construction d'un référentiel géographique ancien : un modèle de graphe agrégé pour intégrer, qualifier et analyser des réseaux géohistoriques". Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1032/document.
Pełny tekst źródłaThe increasing availability of geohistorical data, particularly through the development of collaborative projects is a first step towards the design of a representation of space and its changes over time in order to study its evolution, whether social, administrative or topographical.Geohistorical data extracted from various and heterogeneous sources are highly inaccurate, uncertain or inexact according to the existing terminology. Before being processed, such data should be qualified and spatialized.In this thesis, we propose a solution to this issue by producing reference data. In particular, we focus on Paris historical street networks and its evolution between the end of the XVIIIth and the end of the XIXth centuries.Our proposal is based on a merged structure of multiple representations of data capable of modelling spatial networks at different times, providing tools such as pattern detection in order to criticize, qualify and eventually correct data and sources without using ground truth data but the comparison of data with each other through the merging process.Then, we use the produced reference data to spatialize and integrate other geohistorical data such as social data, by proposing new approaches of data matching and geocoding
Damaj, Samer. "SWH, application "Small-world" à la génération des réseaux d'interconnexion pour les architectures massivement parallèles". Brest, 2011. http://www.theses.fr/2011BRES2076.
Pełny tekst źródłaGraphs with a minimum diameter have applications in the design of building-block switching systems, communication networks, and distributed computer systems. Several methods of constructing directed graphs with a small diameter are proposed. First, the dissertation presents as background several (delta, D) graphs including the Hypercube and de Bruijn. It shows the major disadvantages when implementing these topologies in practice for large scale. To achieve our goal, we propose a regular graph called Small World Heuristic (SWH) suitable for large parallel computers. This graph has a maximum degree ! and a small diameter D, while maintaining an acceptable level of connectivity. We show that this heuristic can connect on short distance thousands of nodes as little as 4 links per node. ̕Finally, we present a new integrated placement and routing algorithm to implement this heuristic on 2D VLSI
Hamon, Ronan. "Analyse de réseaux temporels par des méthodes de traitement du signal : application au système de vélos en libre-service à Lyon". Thesis, Lyon, École normale supérieure, 2015. http://www.theses.fr/2015ENSL1017/document.
Pełny tekst źródłaBike-sharing systems have become essential elements in urban transportation systems of many world's big cities. Thanks to the data generated by these systems, it is possible to obtain a precise characterization of urban cycling, both in terms of transportation and socio-economic aspects. Taking advantage of the recent abundance of data allowed by the current technology, the challenges lie in the development of efficient data analysis method, adapted to these systems. This PhD thesis proposes some answers to this issue, first by methodological developments and second by studying real-world data obtained from the bike-sharing system in Lyon, called Vélo'v.The Vélo'v system can be represented as a network, describing a set of relations between the stations spread over the city. This representation, used for many systems, enables the use of tools from network theory to measure the network structure and understand the underlying mechanisms. Nevertheless, taking into account the dynamic evolution of the structure requires an extension of the classical tools to the temporal case. Parallels between this problem and the field of signal processing can be done, and opens the way to the consideration of connections between the description of the dynamics of temporal networks and those of signals. This work introduces a duality between temporal networks and signals, such that the analysis of the signals using the classical tools of signal processing helps to the characterization of the structure of the corresponding network.This methodology, at the juncture between signal processing and network analysis, is first justified by the study of the Vélo'v network, by comparing different data analysis method and the representation of the system as a temporal network. Then, a method to relabel the vertices of the graph according to the topology of the network is discussed, opening up a duality between networks and signals. This duality is then extended to temporal networks: The analysis of the spectral properties of the signals are studied through a fully automated extraction method, enabling the decomposition of relevant network structure over time
Hain, Horst-Udo. "Phonetische Transkription für ein multilinguales Sprachsynthesesystem". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-81777.
Pełny tekst źródłaThe topic of this thesis is a system which is able to perform a grapheme-to-phoneme conversion for several languages without changes in its architecture. This is achieved by separation of the language dependent knowledge bases from the run-time system. Main focus is an automated adaptation to new languages by generation of new knowledge bases without manual effort with a minimal requirement for additional information. The only source is a lexicon containing all the words together with their appropriate phonetic transcription. Additional knowledge can be used to improve or accelerate the adaptation process, but it must not be a prerequisite. Another requirement is a fully automatic process without manual interference or post-editing. This allows for the adaptation to a new language without even having a command of that language. The only precondition is the pronunciation dictionary which should be enough for the data-driven approach to learn a new language. The automatic adaptation process is divided into two parts. In the first step the lexicon is pre-processed to determine which grapheme sequence belongs to which phoneme. This is the basis for the generation of the training patterns for the data-driven learning algorithm. In the second part mapping rules are derived automatically which are finally used to create the phonetic transcription of any word, even if it not contained in the dictionary. Task is to have a generalisation process that can handle all words in a text that has to be read out by a text-to-speech system
Mimeur, Christophe. "Les traces de la vitesse entre réseau et territoire : approche géohistorique de la croissance du réseau ferroviaire français". Thesis, Dijon, 2016. http://www.theses.fr/2016DIJOL028/document.
Pełny tekst źródłaThe interaction between space and network are frequently questioned in the academic literature, by asking the economical and demographical impacts of a new infrastructure, often studied at the scale of a project. This work aims to investigate the components of the interaction in both large spatial and temporal scales. The hypothesis is that the temporal depth and the national scale could bring new explanations. This work is based on the collect, the exploitation and the analysis of the large spatio-temporal database FRANcE (French Railway Network). It identifies all sections of the network since the 19th century and the population census. This database also contains the traces of the speed, which are novel information for network, and allows the accessibility to become a decisive variable in the explanations. Rather than acquisition new data with an intensive phase of collect, we aim to build a methodological chain to study the two senses of interaction between space and network. It requires the adaptation of data structuration and analysis. The approach of this thesis consists on the growing modelling of the phenomenon, from the comprehension to formalization of data to the analysis, which requires the use of other disciplines. This work uses the graph theory to investigate the two senses of the relationship. It permits to study the network effect in the long run by diversifying the data to identify spatial and temporal ranges. It permits to study the impact of a pre-existing structure in the morphogenesis of the network, by using a dynamic model of network evolution, between diffusion and hierarchical organization. This work aims to understand the link between space and network, where the methodological tools can be adapted to other networks, other times and actual questioning
Hollocou, Alexandre. "Nouvelles approches pour le partitionnement de grands graphes". Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEE063.
Pełny tekst źródłaGraphs are ubiquitous in many fields of research ranging from sociology to biology. A graph is a very simple mathematical structure that consists of a set of elements, called nodes, connected to each other by edges. It is yet able to represent complex systems such as protein-protein interaction or scientific collaborations. Graph clustering is a central problem in the analysis of graphs whose objective is to identify dense groups of nodes that are sparsely connected to the rest of the graph. These groups of nodes, called clusters, are fundamental to an in-depth understanding of graph structures. There is no universal definition of what a good cluster is, and different approaches might be best suited for different applications. Whereas most of classic methods focus on finding node partitions, i.e. on coloring graph nodes so that each node has one and only one color, more elaborate approaches are often necessary to model the complex structure of real-life graphs and to address sophisticated applications. In particular, in many cases, we must consider that a given node can belong to more than one cluster. Besides, many real-world systems exhibit multi-scale structures and one much seek for hierarchies of clusters rather than flat clusterings. Furthermore, graphs often evolve over time and are too massive to be handled in one batch so that one must be able to process stream of edges. Finally, in many applications, processing entire graphs is irrelevant or expensive, and it can be more appropriate to recover local clusters in the neighborhood of nodes of interest rather than color all graph nodes. In this work, we study alternative approaches and design novel algorithms to tackle these different problems. The novel methods that we propose to address these different problems are mostly inspired by variants of modularity, a classic measure that accesses the quality of a node partition, and by random walks, stochastic processes whose properties are closely related to the graph structure. We provide analyses that give theoretical guarantees for the different proposed techniques, and endeavour to evaluate these algorithms on real-world datasets and use cases
Leichtnam, Laetitia. "Detecting and visualizing anomalies in heterogeneous network events : Modeling events as graph structures and detecting communities and novelties with machine learning". Thesis, CentraleSupélec, 2020. http://www.theses.fr/2020CSUP0011.
Pełny tekst źródłaThe general objective of this thesis is to evaluate the interest of graph structures in the field of security data analysis.We propose an end-to-end approach consisting in a unified view of the network data in the form of graphs, a community discovery system, an unsupervised anomaly detection system, and a visualization of the data in the form of graphs. The unified view is obtained using knowledge graphs to represent heterogeneous log files and network traffics. Community detection allows us to select sub-graphs representing events that are strongly related to an alert or an IoC and that are thus relevant for forensic analysis. Our anomaly-based intrusion detection system relies on novelty detection by an autoencoder and exhibits very good results on CICIDS 2017 and 2018 datasets. Finally, an immersive visualization of security data allows highlighting the relations between security elements and malicious events or IOCs. This gives the security analyst a good starting point to explore the data and reconstruct global attack scenarii
Chelly, Magda Lilia. "Propagation d'une position dans les réseaux connectés". Phd thesis, Institut National des Télécommunications, 2011. http://tel.archives-ouvertes.fr/tel-00843587.
Pełny tekst źródłaMartineau, Maxime. "Deep learning onto graph space : application to image-based insect recognition". Thesis, Tours, 2019. http://www.theses.fr/2019TOUR4024.
Pełny tekst źródłaThe goal of this thesis is to investigate insect recognition as an image-based pattern recognition problem. Although this problem has been extensively studied along the previous three decades, an element is to the best of our knowledge still to be experimented as of 2017: deep approaches. Therefore, a contribution is about determining to what extent deep convolutional neural networks (CNNs) can be applied to image-based insect recognition. Graph-based representations and methods have also been tested. Two attempts are presented: The former consists in designing a graph-perceptron classifier and the latter graph-based work in this thesis is on defining convolution on graphs to build graph convolutional neural networks. The last chapter of the thesis deals with applying most of the aforementioned methods to insect image recognition problems. Two datasets are proposed. The first one consists of lab-based images with constant background. The second one is generated by taking a ImageNet subset. This set is composed of field-based images. CNNs with transfer learning are the most successful method applied on these datasets
Solouki, Bonab Vahab. "Polyurethane (PU) Nanocomposites; Interplay of Composition, Morphology, and Properties". Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1542634359353501.
Pełny tekst źródłaIssartel, Yann. "Inférence sur des graphes aléatoires". Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASM019.
Pełny tekst źródłaThis thesis lies at the intersection of the theories of non-parametric statistics and statistical learning. Its goal is to provide an understanding of statistical problems in latent space random graphs. Latent space models have emerged as useful probabilistic tools for modeling large networks in various fields such as biology, marketing or social sciences. We first define an identifiable index of the dimension of the latent space and then a consistent estimator of this index. More generally, such identifiable and interpretable quantities alleviate the absence of identifiability of the latent space itself. We then introduce the pair-matching problem. From a non-observed graph, a strategy sequentially queries pairs of nodes and observes the presence/absence of edges. Its goal is to discover as many edges as possible with a fixed budget of queries. For this bandit type problem, we study optimal regrets in stochastic block models and random geometric graphs. Finally, we are interested in estimating the positions of the nodes in the latent space, in the particular situation where the space is a circle in the Euclidean plane. For each of the three problems, we obtain procedures that achieve the statistical optimal performance, as well as efficient procedures with theoretical guarantees. These algorithms are analysed from a non-asymptotic viewpoint, relying in particular on concentration inequalities