Depuis les travaux précurseurs de Moreno (1934), l’analyse des réseaux est devenue une discipline forte, qui ne se limite plus à la sociologie et qui est à présent appliquée à des domaines très variés tels que la biologie, la géographie ou l’histoire. L’intérêt croissant pour l’analyse des réseaux s’explique d’une part par la forte présence de ce type de données dans le monde numérique d’aujourd’hui et, d’autre part, par les progrès récents dans la modélisation et le traitement de ces données. En effet, informaticiens et statisticiens ont porté leurs efforts depuis plus d’une dizaine d’années sur ces données de type réseau en proposant des nombreuses techniques permettant leur analyse. Parmi ces techniques on note les méthodes de clustering qui permettent en particulier de découvrir une structure en groupes cachés dans le réseau. De nombreux facteurs peuvent exercer une influence sur la structure d’un réseau ou rendre les analyses plus faciles à comprendre. Parmi ceux-ci, on trouve deux facteurs importants: le facteur du temps, et le contexte du réseau. Le premier implique l’évolution des connexions entre les nœuds au cours du temps. Le contexte du réseau peut alors être caractérisé par différents types d’informations, par exemple des messages texte (courrier électronique, tweets, Facebook, messages, etc.) échangés entre des nœuds, des informations catégoriques sur les nœuds (âge, sexe, passe-temps, Les fréquences d’interaction (par exemple, le nombre de courriels envoyés ou les commentaires affichés), et ainsi de suite. La prise en considération de ces facteurs nous permet de capturer de plus en plus d’informations complexes et cachées à partir des données. L’objectif de ma thèse été de définir des nouveaux modèles de graphes aléatoires qui prennent en compte les deux facteurs mentionnés ci-dessus, afin de développer l’analyse de la structure du réseau et permettre l’extraction de l’information cachée à partir des données. Ces modèles visent à regrouper les sommets d’un réseau en fonction de leurs profils de connexion et structures de réseau, qui sont statiques ou évoluant dynamiquement au cours du temps. Le point de départ de ces travaux est le modèle de bloc stochastique (SBM). Il s’agit d’un modèle de mélange pour les graphiques qui ont été initialement développés en sciences sociales. Il suppose que les sommets d’un réseau sont répartis sur différentes classes, de sorte que la probabilité d’une arête entre deux sommets ne dépend que des classes auxquelles ils appartiennent. / Over the last two decades, network structure analysis has experienced rapid growth with its construction and its intervention in many fields, such as: communication networks, financial transaction networks, gene regulatory networks, disease transmission networks, mobile telephone networks. Social networks are now commonly used to represent the interactions between groups of people; for instance, ourselves, our professional colleagues, our friends and family, are often part of online networks, such as Facebook, Twitter, email. In a network, many factors can exert influence or make analyses easier to understand. Among these, we find two important ones: the time factor, and the network context. The former involves the evolution of connections between nodes over time. The network context can then be characterized by different types of information such as text messages (email, tweets, Facebook, posts, etc.) exchanged between nodes, categorical information on the nodes (age, gender, hobbies, status, etc.), interaction frequencies (e.g., number of emails sent or comments posted), and so on. Taking into consideration these factors can lead to the capture of increasingly complex and hidden information from the data. The aim of this thesis is to define new models for graphs which take into consideration the two factors mentioned above, in order to develop the analysis of network structure and allow extraction of the hidden information from the data. These models aim at clustering the vertices of a network depending on their connection profiles and network structures, which are either static or dynamically evolving. The starting point of this work is the stochastic block model, or SBM. This is a mixture model for graphs which was originally developed in social sciences. It assumes that the vertices of a network are spread over different classes, so that the probability of an edge between two vertices only depends on the classes they belong to.

New satellite missions have provided High Resolution (HR) Satellite Image Time Series (SITS), offering detailed spatial, spectral, and temporal information for effective monitoring of diverse Earth features including weather, landforms, oceans, vegetation, and agricultural practices. SITS can be used for an accurate understanding of the Land Cover (LC) behavior and providing the possibility of precise mapping of LCs. Moreover, HR SITS presents an unprecedented possibility for the creation and modification of HR Land Cover Change (LCC) and Land Cover Transition (LCT) maps. For the long-term scale, spanning multiple years, it becomes feasible to analyze LCC and the LCTs occurring between consecutive years. Existing methods in literature often analyze bi-temporal images and miss the valuable multi-temporal/multi-annual information of SITS that is crucial for an accurate SITS analysis. As a result, HR SITS necessitates a paradigm shift in processing and methodology development, introducing new challenges in data handling. Yet, the creation of techniques that can effectively manage the high spatial correlation and complementary temporal resolutions of pixels remains paramount. Moreover, the temporal availability of HR data across historical and current archives varies significantly, creating the need for an effective preprocessing to account for factors like atmospheric and radiometric conditions that can affect image reflectance and their applicability in SITS analysis. Flexible and automatic SITS analysis methods can be developed by paying special attention to handling big amounts of data and modeling the correlation and characterization of SITS in space and time. Novel methods should deal with data preparation and pre-processing at large-scale from end-to-end by introducing a set of steps that guarantee reliable SITS analysis while upholding the computational efficiency for a feasible SITS analysis. In this context, the recent strides in deep learning-based frameworks have demonstrated their potential across various image processing tasks, and thus the high relevance for addressing SITS analysis. Deep learning-based methods can be supervised or unsupervised considering their learning process. Supervised deep learning methods rely on labeled training data, which can be impractical for large-scale multi-temporal datasets, due to the challenges of manual labeling. In contrast, unsupervised deep learning methods are favored as they can automatically discover temporal patterns and changes without the need for labeled samples, thereby reducing the computational load, making them more suitable for handling extensive SITS. In this scenario, the objectives of this thesis are mainly three. Firstly, it seeks to establish a robust and reliable framework for the precise mapping of LCs by designing novel techniques for time series analysis. Secondly, it aims to utilize the capacities of unsupervised deep learning methods, such as pretrained Convolutional Neural Networks (CNNs), to construct a comprehensive methodology for Change Detection (CD), thereby mitigating complexity and reducing computational requirements in comparison with supervised methods. This involves the efficient extraction of spatial, spectral, and temporal features from complex multi-temporal, multi-spectral SITS. Lastly, the thesis endeavors to develop novel methods for analyzing LCCs occurring over extended time periods, spanning multiple years. This multifaceted approach encompasses the detection of changes, timing identification, and classification of the specific types of LCTs. The efficacy of the innovative methodologies and associated techniques is showcased through a series of experiments conducted on HR SITS datasets, including those from Sentinel-2 and Landsat. These experiments reveal significant enhancements when compared to existing methods that represent the current state-of-the-art.

Made available in DSpace on 2014-12-17T14:06:55Z (GMT). No. of bitstreams: 1 FranciscoJPF.pdf: 1681554 bytes, checksum: 4238148885bafd3e26a8d8ca7de20466 (MD5) Previous issue date: 2010-08-07 / Nowadays the environmental issues are increasingly highlighted since the future of humanity is dependent on the actions taken by man. Major efforts are being expended in pursuit of knowledge and alternatives to promote sustainable development without compromising the environment. In recent years there has been a marked growth in the development of reinforced composite fiber plants, as an alternative for economic and ecological effects, especially in the substitution of synthetic materials such as reinforcement material in composites. In this current study the chemical- physical or (thermophysics )characteristics of the babassu coconut fiber, derived from the epicarp of the fruit (Orbignyda Phalerata), which the main constituents of the fiber: Klason lignin, insoluble, cellulose, holocellulose, hemicellulose and the content of ash and moisture will be determined. A study was conducted about the superficial modification of the fibers of the epicarp babassu coconut under the influence of chemical treatment by alkalinization, in an aqueous solution of NaOH to 2.5% (m/v) and to 5.0% to improve the compatibility matrix / reinforcement composite with epoxy matrix. The results of the changes occurred in staple fibers through the use of the techniques of thermogravimetric analyses (TG) and differential scanning calorimetry (DSC). The results found on thermal analysis on samples of fiber without chemical treatment (alkalinities), and on fiber samples treated by alkalinization show that the proposed chemical treatment increases the thermal stability of the fibers and provides a growth of the surface of area fibers, parameters that enhance adhesion fiber / composite. The findings were evaluated and compared with published results from other vegetable fibers, showing that the use of babassu coconut fibers has technical and economic potential for its use as reinforcement in composites / Atualmente as quest?es ambientais ganham destaque cada vez mais acentuado, j? que o futuro da humanidade est? dependente das a??es tomadas hoje pelo homem. Grandes esfor?os est?o sendo despendidos na busca de conhecimentos e solu??es alternativas sustent?veis que promova o desenvolvimento sem comprometimento do meio ambiente. Nos ?ltimos anos tem havido um crescimento acentuado no desenvolvimento de comp?sitos refor?ados por fibras vegetais, como uma alternativa econ?mica e ecol?gica, principalmente, na substitui??o de materiais sint?ticos, como material de refor?o em comp?sitos. No presente trabalho foram analisadas as caracter?sticas qu?mico-f?sicas de fibra oriundas do epicarpo do coco baba?u (Orbignyda Phalerata), sendo determinados os principais teores dos constituintes da fibra: lignina Klason insol?vel, celulose, holocelulose, hemicelulose e os teores de cinzas e de umidade. Foi realizado um estudo da modifica??o superficial das fibras do epicarpo do coco baba?u sob efeito de tratamento qu?mico por alcaliniza??o, em solu??o aquosa de NaOH a 2,5% (m/v) e a 5,0% (m/v), visando melhorar a compatibiliza??o matriz/refor?o em comp?sito com a matriz de ep?xi. Os resultados das modifica??es ocorridas nas fibras foram estudados atrav?s de t?cnicas de termogravimetria (TG) e de calorimetria explorat?ria diferencial (DSC). Os resultados encontrados nas an?lises t?rmicas em amostras de fibras sem tratamento qu?mico e em amostras de fibras tratadas por alcaliniza??o mostram que o tratamento qu?mico proposto aumentou a estabilidade t?rmica das fibras e proporcionou um crescimento na ?rea superficial das fibras, par?metros que melhoram a ades?o fibra/comp?sito. Os resultados obtidos foram avaliados e comparados com resultados publicados de outras fibras vegetais, mostrando que a utiliza??o das fibras de coco baba?u tem potencialidades t?cnicas e econ?micas para o seu uso como refor?o de comp?sitos

The aim of this master thesis is a design of the pedestrian bridge across the highway. The bridge is formed by a slab structure of 6 spans with lenghts from 9 to 51 m. The main spans are suspended on a V shape pylon. The deck of the span across the highway is assambled of precast segments and composite deck slab. The deck is in the lenghtways kept in the parabolic arch. The model of the construction is made in software ANSYS, the solution was done non-linear. The design and assessment are according to the europien standard.

Bacterial endophytes are the organisms that live inside the plant for a full or a part of their life cycle. Endophytic bacteria have captured the interest of agriculture industry due to their plant beneficial properties, such as synthesis of phytohormones, solubilization of soil nutrients, and alleviation of biotic and abiotic stresses. Several studies have reported that stress tolerant endophytic bacteria can work with a similar performance as non-stressed conditions when inoculated to the plants under stressed conditions. Combination of abiotic stresses such as salinity, drought and low nitrogen stress can have additive or agonistic effects on bacterial and plant growth, and their interactions. However, very few studies have reported the impact of combined stress on endophytic bacterial assisted plant growth promotion. Therefore, understanding the underlying mechanisms of endophytic bacterial assisted plant’s tolerance abiotic stresses may provide the means of better exploiting the beneficial abilities of endophytic bacteria in agricultural production. Thus, the aim of this thesis was to study the stress tolerance mechanisms, beneficial characteristics, and plant growth promotion characteristics of endophytic bacteria under individual and combined abiotic stresses. Transcriptome analysis of endophytic bacteria revealed that tolerance mechanisms to deal with one kind of stress is different than concurrent stresses. Salinity and drought stress largely modulated the genes involved in flagellar assembly and membrane transport, showing reduced motility under stress conditions to preserve the energy. Additionally, bacterial endophyte that can fix nitrogen was studied with maize plant growth promotion under drought and low nitrogen stress conditions. The results suggested that diazotrophic bacterial endophyte can promote plant growth under moderate individual and combined stress conditions. Plant growth promoting endophytic bacteria can be utilized as an efficient tool to increase crop production under individual and concurrent abiotic stresses.

The research focuses on analysis and subsurface imaging of siliciclastics rocks on steam-affected 3D poststack seismic data, merged from different vintages, from the Temblor Formation in the Coalinga heavy oil reservoir in the San Joaquin basin, California. The objective was identification, delineation, and demarcation of reservoir heterogeneities by seismostratigraphic and seismogeomorphic analysis. The proximity of the San Andreas Transforms greatly controlled basin evolution and caused substantial reservoir heterogeneity by changing the depositional environment from shallow marine to near-shore fluvial. Moreover, two unconformities dissect the reservoir interval. The seismic dataset exhibits erratic, distorted reflection strengths and amplitudes caused by steam-injection-aided production. A petrophysical analysis based on Gassmann fluid substitution suggests a 27% P-wave velocity decrease in steam-saturated intervals. Seismic to well log ties were problematic and vexing due to the resulting statics, wavelet changes, and line mismatches. Mapping and flattening on a deeper horizon, however, allowed mapping of the internal unconformities and well ties which were crucial for seismostratigraphic sequence identification. Visualization of seismic attributes brought out stratification patterns and two distinct, laterally and vertically extensive, porous, and interconnected facies tracts interpreted as incised valley fills and tidal-to-subtidal deposits as evidenced by bright, steam related amplitudes. Seismic attribute analysis, Geobody Visualization and Interpretation, and structure and isochron maps brought out two prominent channel-systems, recut and restacked in the central part of the area. These deposits were identified on seismic data and correlated to high-gamma coarsening-upward sands on logs and cores. The deeper one, shifting towards SSE with depth, lies between the Base Temblor and Buttonbed unconformities both in the southwestern and northwestern parts of the study area and is scattered in the western-central portion. The shallower one originates in southwestern corner below the Top Temblor unconformity shifts towards ESE-SE with depth, and runs nearly parallel to the Top Temblor unconformity. It cuts across the Valv unconformity in central part creating a channel incision, and follows the Buttonbed unconformity towards the north. The investigation segmented the reservoir into channels, non-channel bearing, and unconformity-bounded subunits which will allow the operator to improve steam injection and optimize placement of oil producing infill wells. / Ph. D.

Made available in DSpace on 2016-12-12T20:27:38Z (GMT). No. of bitstreams: 1 Camila Bianka Silva Bastos.pdf: 1963598 bytes, checksum: bee88eacc3f6e3c327425297316a691d (MD5) Previous issue date: 2015-02-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This dissertation presents a study of the operation of two different three-phase grid-connected test-grids with the connection of a 1MWp photovoltaic system. Two analysis methods are used to evaluate the impacts of this photovoltaic systeM, these methods being conventional static analysis and the analysis known as Quasi-Static Time-Series Analysis. Despite the fact that all grids have unique characteristics, it is important to use test-grids, which simulate the real grid characteristics, to analyze the kinds of problems that can occur and then look for alternatives, if necessary. The impacts evaluated are related to the system losses, minimized with the allocation study of the generation on the grid, voltage profile and tap position curve, when automatic load tap changers are used. It was verified that the photovoltaic system interconnection point is the most influenced one after its connection to the grid. The Quasi-Static Time-Series Analysis allow the correct evaluation of the load-generation interaction, running the time series power flow through estimated data for the load and irradiance curves during 168 hours. The conventional static analysis only considers critical operation conditions, like minimum and maximum load, and no generation or maximum generation, and does not evaluate different case scenarios that occur in reality. The photovoltaic systems can bring many advantages to the electric systems, like the improvement on the final consumer voltage profile, line losses reduction, and also environmental impacts reduction. However, with the increase of distributed photovoltaic generation on the electrical grid, it s necessary to be aware of the impacts that this may cause by performing interconnection studies. / Esta dissertação apresenta um estudo da operação de uma rede teste trifásica de média tensão com a interligação de um sistema fotovoltaico de 1,0 MWp. Dois métodos de análise são utilizados para avaliar os impactos deste sistema fotovoltaico, sendo estes métodos as análises estáticas convencionais eas análises conhecidas como Quasi-Static Time-Series Analysis. Apesar de cada rede elétrica apresentar características únicas, é importante a utilização de sistemas testes, que simulam as características de sistemas reais, para analisar que tipos problemas podem surgir e então buscar alternativas, se necessário. Os impactos avaliados se referem às perdas no sistema, minimizadas com a correta alocação da geração, perfil de tensão e curva de posição do tap, no caso de transformador com comutação automática de tap. Contata-se que o ponto de conexão do sistema fotovoltaico é o mais influenciado pela sua conexão à rede. As análises QSTS possibilitam avaliar corretamente a iteração entre carga e geração, efetuando o fluxo de potência consecutivo através de dados estimados para as curvas de carga e de irradiância solar ao longo de 168 horas. Já as análises convencionais consideram apenas condições críticas de operação, como por exemplo, carga leve ou nominal e geração nula ou máxima, não avaliando então diferentes cenários de operação que ocorrem na prática. Os sistemas fotovoltaicos podem trazer muitos benefícios aos sistemas elétricos, como melhoria do perfil de tensão de atendimento ao consumidor, redução de perdas nas linhas, além da redução nos impactos ambientais. Entretanto, com o aumento de geração fotovoltaica distribuída na rede, é necessário estar atento aos impactos que isto pode causar através de estudos de interconexão.

Fires following earthquake (FFE) have historically produced enormous post-earthquake damage and losses in terms of lives, buildings and economic costs, like the San Francisco earthquake (1906), the Kobe earthquake (1995), the Turkey earthquake (2011), the Tohoku earthquake (2011) and the Christchurch earthquakes (2011). The structural fire performance can worsen significantly because the fire acts on a structure damaged by the seismic event. On these premises, the purpose of this work is the investigation of the experimental and numerical response of structural and non-structural components of steel structures subjected to fire following earthquake (FFE) to increase the knowledge and provide a robust framework for hybrid fire testing and hybrid fire following earthquake testing. A partitioned algorithm to test a real case study with substructuring techniques was developed. The framework is developed in MATLAB and it is also based on the implementation of nonlinear finite elements to model the effects of earthquake forces and post-earthquake effects such as fire and thermal loads on structures. These elements should be able to capture geometrical and mechanical non-linearities to deal with large displacements. Two numerical validation procedures of the partitioned algorithm simulating two virtual hybrid fire testing and one virtual hybrid seismic testing were carried out. Two sets of experimental tests in two different laboratories were performed to provide valuable data for the calibration and comparison of numerical finite element case studies reproducing the conditions used in the tests. Another goal of this thesis is to develop a fire following earthquake numerical framework based on a modified version of the OpenSees software and several scripts developed in MATLAB to perform probabilistic analyses of structures subjected to FFE. A new material class, namely SteelFFEThermal, was implemented to simulate the steel behaviour subjected to FFE events.