Dissertations / Theses on the topic 'Diffusion prediction'
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1
D’Agostino, Carmine, Geoff D. Moggridge, Lynn F. Gladden, and Mick D. Mantl. "Prediction of mutual diffusion coefficients in non-ideal binary mixtures from PFG-NMR diffusion measurements." Diffusion fundamentals 20 (2013) 109, S. 1-2, 2013. https://ul.qucosa.de/id/qucosa%3A13698.
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D’Agostino, Carmine, Geoff D. Moggridge, Lynn F. Gladden, and Mick D. Mantl. "Prediction of mutual diffusion coefficients in non-ideal binary mixtures from PFG-NMR diffusion measurements." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-184023.
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Nowicki, Timothy. "Statistical model prediction of fatigue life for diffusion bonded Inconel 600 /." Online version of thesis, 2008. http://hdl.handle.net/1850/7984.
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Pirot, Fabrice. "Analyse, mesure et prediction de la diffusion dans le stratum corneum humain." Besançon, 1996. http://www.theses.fr/1996BESA3710.
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Zhu, Qingyong, Geoffrey D. Moggridge, and Carmine D’Agostino. "A local composition model for the prediction of mutual diffusion coefficients in binary liquid mixtures from tracer diffusion coefficients." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-198798.
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Zhu, Qingyong, Geoffrey D. Moggridge, and Carmine D’Agostino. "A local composition model for the prediction of mutual diffusion coefficients in binary liquid mixtures from tracer diffusion coefficients: A local composition model for the prediction of mutual diffusioncoefficients in binary liquid mixtures from tracer diffusion coefficients." Diffusion fundamentals 24 (2015) 58, S. 1, 2015. https://ul.qucosa.de/id/qucosa%3A14577.
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Long, Xiaoyan. "Prediction of shear strength and vertical movement due to moisture diffusion through expansive soils." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4313.
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This dissertation presents an investigation of engineering behavior of expansive
soils. An analytical study was undertaken for the development and modification of a
Windows-based two-dimensional finite element computer program FLODEF that
performs a sequentially coupled flow-displacement analysis for the prediction of
moisture diffusion and the induced volume change in soils supporting various elements
of civil infrastructure. The capabilities of the model are illustrated through case studies
of shear strength envelope forecast and parametric studies of transient flow-deformation
prediction in highway project sites to evaluate the effectiveness of engineering treatment
methods to control swell-shrink deformations beneath highway pavements. Numerical
simulations have been performed to study the field moisture diffusivity using a
conceptual model of moisture diffusion in a fractured soil mass. A rough correlation
between field and the laboratory measurements of moisture diffusion coefficients has
been presented for different crack depth patterns.
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Reynier, Alain. "Modelisation et prediction de la migration des additifs des emballages alimentaires." Reims, 2000. http://www.theses.fr/2000REIMS004.
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La prediction de la migration par modelisation mathematique peut etre envisagee pour verifier la conformite d'un materiau plastique utilise en contact alimentaire et pour preciser l'incidence des phenomenes physico-chimiques impliques dans la migration. Dans une premiere partie, la prediction du coefficient de diffusion d'une molecule dans une matrice polymere a ete etudiee a partir de mesures experimentales de coefficients de diffusion. Un panel de composes a ete teste dans quatre polyolefines (vierges puis gonflees par un simulateur d'aliment gras). Ceci a permis de mettre en evidence l'effet du gonflement sur la diffusion. La correlation des diffusivites a la masse molaire des migrants a permis de determiner des groupes de comportement (diffusion rapide par reptation ou plus lente par sauts) selon la forme des molecules. Le concept de volume fractionne pondere par un facteur de forme a ete introduit afin de tenir compte de ces differences liees a la geometrie des migrants. Nous avons ensuite propose une modelisation de la migration qui, pour la premiere fois, prend en compte simultanement les principaux phenomenes impliques dans la migration (evolution de la diffusivite liee au gonflement du materiau par le simulateur sorbe, limitations cinetiques de transfert de matieres a l'interface). Ce modele a ete valide par comparaison a un essai de migration et a permis de montrer les limites d'utilisation des modeles simplifies. Il a de plus ete adapte au cas de l'extraction par solvant en introduisant la notion de solubilite potentielle du solvant dans le polymere, variant au cours du temps en fonction de la concentration en solvant sorbe. Enfin, ce travail propose une evolution de l'approche predictive en discussion dans le cadre de la reglementation europeenne en s'appuyant sur la prediction statistique de coefficients de diffusions surestimes et sur l'utilisation d'un modele adapte a la complexite du processus de migration.
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Chang, Hojoon. "Prediction of Soot Formation in Laminar Opposed Diffusion Flame with Detailed and Reduced Reaction Mechanisms." Thesis, Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4922.
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The present work focuses on a computational study of a simplified soot model to predict soot production and destruction in methane/oxidizer (O2 and N2) and ethylene/air flames using a one-dimensional laminar opposed diffusion flame setup. Two different detailed reaction mechanisms (361 reactions and 61 species for methane/oxidizer flame and 527 reactions and 99 species for ethylene/air flame) are used to validate the simplified soot model in each flame. The effects of strain rate and oxygen content on the soot production and destruction are studied, and the soot related properties such as soot volume fraction, particle number density and particle diameter are compared with published results. The results show reasonable agreement with data and that the soot volume fraction decreases with higher strain rate and lower oxygen content. The simplified soot model has also been used with two reduced reaction mechanisms (12-step, 16-species for methane flame
and 20-species for ethylene flame) since such reduced mechanisms are computationally more efficient for practical application. The profiles of the physical properties and the major species are in excellent agreement with the results using the detailed reaction mechanisms. However, minor hydrocarbon-species such as acetylene (C2H2) that is the primary pyrolysis species in the simplified soot model is significantly over predicted and this, in turn, results in an over-prediction of soot production. Finally, the reduced reaction mechanism is modified to get more accurate prediction of the minor hydrocarbon-species. The modified reduced reaction mechanism shows that the soot prediction can be improved by improving the predictions of the key minor species.
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Atwood, Robert Carl. "A combined cellular automata and diffusion model for the prediction of porosity formation during solidification." Thesis, Imperial College London, 2001. http://hdl.handle.net/10044/1/11433.
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Emadi, Mohammad Ali. "Prediction of molecular diffusion coefficients of gases in hydrocarbon liquids at high pressure and temperature." Thesis, University of Surrey, 2004. http://epubs.surrey.ac.uk/843592/.
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Mass transfer by molecular diffusion is the basic physical mechanism underlying many important areas of chemical engineering and petroleum engineering. In recent years, the problem of mass transfer by the mechanism of molecular diffusion in oil reservoirs, when a non-equilibrium gas is injected into the reservoir, has become increasingly important. In oil recovery projects, gas is injected into oil reservoirs for different reasons such as maintenance of reservoir pressure and enhanced recovery of oil. In these two cases the rate of dissolution of a gas such as methane in a quiescent body of hydrocarbon oil is controlled primarily by the rate of diffusion of the dissolved gas from the gas-oil interface into the body of the liquid phase. In all the above situations, molecular diffusion of gas into liquid or transfer of dissolved gas between enriched and heavier liquid phase due to differences in compositional gradients between gas and liquid phases is important. The most important property required to determine the rate of mass transfer between the two phases in all these cases is the molecular diffusion coefficient at high pressure and temperature. The present investigation is aimed at a systematic study of the mechanism of molecular diffusion of gases in liquids by measuring the diffusion coefficients of methane in dodecane and in a typical Iranian crude oil up to a pressure of 35 MPa and at several temperatures. All tests are conducted in an accurate high-pressure diffusion cell with "finite-domain" moving boundary behavior. The data acquired is used to assess the predictions of various available correlations for diffusion coefficients. Several liquid hydrocarbon swelling tests comprising dodecane and a typical Iranian crude oil as liquids and methane as gas are performed and swelling heights of liquid as a result of gas molecular diffusion are measured at various temperatures (T=25°C to82°C ) and pressures (P=3.2 to 35 MPa), characterized by a sharp increase in volume followed by gradual increase toward the saturation concentration of methane in the liquid phase. A mathematical model is developed to calculate diffusivities using semi-infinite boundary conditions, hi this model, a variable power profile with time is introduced to allow for the moving interface boundary. The current solutions offer significant improvement over those in previous literature that assume a steady-state interface boundary condition with a parabolic concentration profile. The proposed model offers excellent predictions of experimental data for diffusion coefficients of methane-dodecane and crude oil systems. A computer program using a neural network model is set-up to predict the dimensionless diffusivity for special use with more complex systems such as crude oil reservoir flows in fractures and matrix conditions. The results obtained by this software show about +/- 2% deviation in comparison with the experimental data from the diffusion cell experiments.
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Jackson, Eric Alan. "Towards a Prediction of Landscape Evolution from Chemical Weathering and Soil Production." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1516116071724445.
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Kuwahara, Ryo. "A Predictor of Tumor Recurrence in Patients With Endometrial Carcinoma After Complete Resection of the Tumor: The Role of Pretreatment Apparent Diffusion Coefficient." Kyoto University, 2020. http://hdl.handle.net/2433/253483.
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Wang, Yanxin. "Hypoxic-ischemic injury in the neonatal rat model prediction of irreversible infarction size by Diffusion Weighted MR Imaging /." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B35757577.
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Truc, Olivier. "Prediction of chloride penetration into saturates concrete - multi-species approach." Toulouse, INSA, 2000. http://www.theses.fr/2000ISAT0019.
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Le cout entraine par la rehabilitation des ouvrages en beton arme corrodes est une source d'inquietude mondiale. Les mecanismes de reaction-diffusion impliques durant le transport des ions chlorure, qui sont a l'origine de la corrosion des armatures, sont donc etudies dans le cas d'un beton sature. La litterature nous informe que de nombreuses methodes experimentales ainsi que des modeles existent afin de comprendre et de decrire le transport de ces ions. Toutefois, il apparait que differents parametres obtenus empiriquement sont souvent difficiles a comparer entre eux et certaines observations experimentales restent inexpliquees. A partir de ce constat, une theorie encore peu utilisee dans le domaine du genie civil, appelee l'approche multi-especes, est presentee. Cette approche, qui prend en compte les interactions entre les differentes especes ioniques presentes dans la solution interstitielle du beton, a ete utilisee pour modeliser la diffusion et la migration de plusieurs especes ioniques dans des milieux poreux satures. Un nouveau modele numerique, appele msdiff, pour multi-species diffusion, a ete developpe afin de simuler diverses situations qui impliquent le transport des ions chlorure. Grace a msdiff, divers resultats experimentaux trouves dans la litterature et qui n'etaient pas tres bien compris, peuvent maintenant etre expliques. Ensuite, msdiff a ete utilise pour simuler des essais d'immersion effectues sur differents betons. Les simulations montrent, a l'aide d'une etude de sensibilite, quels sont les phenomenes qui ont le plus d'influence sur le transport des ions chlorure. Parmi eux, la fixation des ions par le beton et la composition de la solution interstitielle semblent avoir le plus grand effet. Enfin, les simulations demontrent clairement qu'il n'est pas raisonnable d'utiliser une methode empirique pour predire la vitesse de penetration des ions chlorure. L'utilisation des lois de fick pour predire a long terme est donc fortement remise en cause.
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Jungkuist, David Alan. "Simulation of Enviro-mechanical Durability for Life Prediction of E-Glass/Vinyl Ester Composites using a Bridge Service Environment." Thesis, Virginia Tech, 2000. http://hdl.handle.net/10919/32791.
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In order for composites to become an accepted material for infrastructure application, life prediction and durability must be understood. The majority of studies have examined the strength and fatigue response of composites under hot and/or moist conditions. Various researchers have also studied life prediction methods for composite materials under fatigue, primarily for high performance applications. Little work has been done to study durability under combined service conditions for composites used in civil infrastructure applications.
This thesis focuses on the development of a life prediction model for use with fiber reinforced polymer composites in bridge service environments. The Tomâ s Creek Bridge of Blacksburg, VA is used as a guiding case study. First, the tensile properties of the composite were studied as a function of temperature and moisture. Damage accumulation was studied as a function of cyclic loading and temperature cycles. The enviro-mechanical conditions, including moisture, temperature and fatigue loading, were then used in a computer simulation to predict the life of a vinyl ester/glass composite under an approximate bridge service environment.
Finally, a laboratory simulation was conducted that approximates the temperature and humidity that is seen at the Tomâ s Creek Bridge, but in an accelerated time frame. A multi-stress fatigue pattern, mimicking cars and trucks passing over the bridge, was used. One year of conditions was accelerated to approximately six hours and thirty-three minutes using a servo-hydraulic test frame and environmental chamber.
The final results showed that life prediction methodology conservatively predicted the lifetime of a vinyl ester/glass composite under the enviro-mechanical conditions. The damage of the composite was predominately driven by cyclic loading. The environmental conditions of moisture and temperature had only a small affect on the lifetime of the composite. This lack of environmental sensitivity is largely due to the durability of the resin system.Master of Science
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Goswami, Tarun. "Sublingual drug delivery: In vitro characterization of barrier properties and prediction of permeability." Scholarly Commons, 2008. https://scholarlycommons.pacific.edu/uop_etds/2370.
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Sublingual administration of drugs offers advantages including avoidance of first pass metabolism and quick absorption into the systemic circulation. In spite of being one of the oldest routes of drug delivery, there is dearth of literature on characterization of the barrier properties of the sublingual mucosa. Therefore, the aim of this research was to gain an insight into the barrier properties of the porcine sublingual mucosa. The studies conducted in this dissertation research focused on an important aspect of sublingual permeation, the dependence of permeability on different physicochemical properties of the permeant such as the degree of ionization, distribution coefficient and molecular weight/size on drug transport across sublingual mucosa. Further the data from the sublingual permeation of model compounds was used in development of a predictive model which provided us with some understanding regarding the important descriptors required for sublingual drug delivery. A series of β-blockers were employed as the model drugs to study the dependence of permeability on lipophilicity across the sublingual mucosa. Eighth different β-blockers with log D (distribution coefficient) values ranging from -1.30 to 1.37 were used in this study. The most hydrophilic drug atenolol showed the lowest permeability (0.19 ± 0.04 x 10 -6 ) cm/sec and the most lipophilic drug propranolol showed the highest permeability (38.25 ± 4.30 x 10 -6 ) cm/sec. The log-log plot of permeability coefficient and the distribution coefficient showed a linear relationship. It was concluded that the increase in lipophilicity results in improved partitioning across the lipid bilayers of sublingual mucosa which results in increased permeation for the drugs. As the sublingual mucosa contains a significant amount of the polar lipids bonded with water molecules, therefore, it was hypothesized that the hydrophilic or ionized permeants will have significant permeation across the sublingual mucosa. The objective of this research was to study the effect of ionization on permeation across sublingual mucosa using a model drug nimesulide. Based on the relationship between the permeability coefficient and distribution coefficient of nimesulide at different pH, the lipoidal route was suggested as the dominant transport route for nimesulide across the sublingual mucosa. The contribution of individual ionic species of nimesulide to the total drug flux was quantitatively delineated. It was observed that the ionized species of nimesulide contributes significantly to the total flux across the sublingual mucosa. The contribution of the ionized species to total flux was almost (90%) at a pH where the drug was almost completely ionized. Polyethylene glycols (PEGs) were used as the model permeants to study the dependence of permeability on molecular weight. An inverse relationship between molecular weight and permeability coefficients was observed. This relationship was used to estimate the molecular weight cut off for the sublingual mucosa. The molecular weight cut off was estimated to be around 1675 daltons. Further, the Renkin function was used to estimate the theoretical pore size of the sublingual mucosa and the pore size of the sublingual mucosa was estimated to be around 30–53 Å based on two separate calculations using the radius of gyration and Stokes-Einstein radius for PEG molecules, respectively. No specific model is present in literature to predict the in vitro sublingual drug permeability. In this dissertation a specific model was developed and validated by performing permeation studies of 14 small molecules across the porcine sublingual mucosa. It was shown that the lipophilicity (logD 6.8 ) and the number of hydrogen bond donors (HBD) were the most significant descriptors affecting sublingual permeability. Research conducted in this dissertation provided an in-depth understanding about the barrier properties of the porcine sublingual mucosa and role of different physicochemical properties on sublingual transport. Such an understanding will hopefully expand the suitable lead candidates for sublingual delivery.
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Liu, Xiaomo. "Online Knowledge Community Mining and Modeling for Effective Knowledge Management." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/50646.
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More and more in recent years, activities that people once did in the real world they now do in virtual space. In particular, online communities have become popular and efficient media for people all over the world to seek and share knowledge in domains that interest them. Such communities are called online knowledge communities (OKCs). Large-scale OKCs may comprise thousands of community members and archive many more online messages. As a result, problems such as how to identify and manage the knowledge collected and how to understand people\'s knowledge-sharing behaviors have become major challenges for leveraging online knowledge to sustain community growth.
In this dissertation I examine three important factors of managing knowledge in OKCs. First, I focus on how to build successful profiles for community members that describe their domain expertise. These expertise profiles are potentially important for directing questions to the right people and, thus, can improve the community\'s overall efficiency and efficacy. To address this issue, I present a comparative study of models of expertise profiling in online communities and identify the model combination that delivers the best results.
Next, I investigate how to automatically assess the information helpfulness of user postings. Due to the voluntary nature of online participation, there is no guarantee that all user-generated content (UGC) will be helpful. It is also difficult, given the sheer amount of online postings, for knowledge seekers to find information quickly that satisfies their informational needs. Therefore, I propose a theory-driven text classification framework based on the knowledge adoption model (KAM) for predicting the helpfulness of UGC in OKCs. I test the effectiveness of this framework at both the thread level and the post level of online messages.
Any given OKC generally has a huge number of individuals participating in online discussions, but exactly what, where, when and how they seek and share knowledge are still not fully understood or documented. In the last part of the dissertation, I describe a multi-level study of the knowledge-sharing behaviors of users in OKCs. Both exploratory data analysis and network analysis are applied to thread, forum and community levels of online data. I present a number of interesting findings on social dynamics in knowledge sharing and diffusion. These findings potentially have important implications for both the theory and practice of online community knowledge management.Ph. D.
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Bohlin, Johannes. "Lifetime prediction of a polymeric propellant binder using the Arrhenius approach." Thesis, Uppsala universitet, Tillämpad materialvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-446609.
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The thermal-oxidative degradation of a crosslinked hydroxy-terminated polybutadiene (HTPB)/cycloaliphatic diisocyanate (H12MDI) based polymer, which is commonly used as a polymeric binder in propellants, is investigated at temperatures from 95°C to 125°C with the aim of estimating the lifetime of the material in storage conditions (20°C) using the Arrhenius approach. Furthermore, the effect of antioxidants and to a lesser extent plasticizer on the degradation process was also studied. Diffusion-limited oxidation (DLO) was theoretically modelled and DLO conditions were estimated by gathering oxygen permeability and consumption data from similar studies. It was concluded that DLO-effects might be present at the highest experiment temperature (125°C) depending on the actual properties of the material investigated. The mechanical degradation was monitored by conducting tensile tests in a DMA apparatus and photographs using a microscope was taken to examine potential DLO effects. The degradation process of the stabilized polymer (with antioxidant) did not showcase Arrhenius behaviour, which was confirmed by the failure to construct a satisfactory mastercurve. This was most likely due to loss of antioxidants, resulting in autocatalytic oxidation(acceleration of the oxidation process). However, the induction period of the stabilized polymer showcased Arrhenius behaviour in the temperature region 95-125°C with an ~E_a = 90 kJ/mol. If the activation energy E_a is assumed to remain constant, the lifetime at ambient temperature (20°C) is predicted to be approximately 176 Years for a 2mm thick sample. However, this is probably an overestimation since curvature in the Arrhenius plot has been observed for many rubber materials in the lower temperature region. Assuming the E_a drops from ~90 kJ/mol to~71 kJ/mol, a more conservative lifetime prediction of 58 Years was estimated.
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Hamadeh, Nizar. "Le développement de la loi de diffusion des incendies en modélisant le niveau de danger et son évolution dans le temps. : comparaison avec des données expérimentales dans les forêts libanaises." Thesis, Angers, 2017. http://www.theses.fr/2017ANGE0060/document.
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Les incendies de forêt sont l'un des phénomènes les plus complexes auxquels sont confrontées nos sociétés. Le Liban, faisant partie du Moyen-Orient, est en train de perdre dramatiquement ses forêts vertes principalement en raison de graves incendies. Cette thèse étudie le phénomène des incendies de forêt. Elle propose des nouveaux modèles et méthodologies pour remédier à la crise des incendies de forêts, en particulier au Liban et en Méditerranée. Elle est divisée en deux parties principales: nouvelles approches de la prévision des incendies de forêt et développement d'un nouveau modèle de diffusion du feu plus fidèle du cas réel. La première partie est subdivisée en 3 chapitres. Le premier chapitre présente une étude analytique des modèles métrologiques les plus utilisés qui permettent de prédire les incendies de forêt. Dans le deuxième chapitre, nous appliquons cinq méthodes de techniques d’exploration de données: Réseaux de neurones, arbre de décision, floue logique, analyse discriminante linéaire et méthode SVM. Nous cherchons à trouver la technique la plus précise pour la prévision des incendies de forêt. Dans le troisième chapitre, nous utilisons différentes techniques d'analyse de données corrélatives (Régression, Pearson, Spearman et Kendall-tau) pour évaluer la corrélation entre l'occurrence d'incendie et les données météorologiques (température, point de rosée, température du sol, humidité, précipitation et vitesse du vent). Cela permet de trouver les paramètres les plus influents qui influencent l'occurrence de l’incendie, ce qui nous amène à développer un nouveau Indice Libanais de Risques d'Incendie (IL). L'indice proposé est ensuite validé à partir des données météorologiques pour les années 2015-2016. La deuxième partie est subdivisée en 3 chapitres. Le premier chapitre passe en revue les caractéristiques du comportement de feu et sa morphologie; il se concentre sur la validité des modèles mathématique et informatique de comportement de feu. Le deuxième chapitre montre l'importance des automates cellulaires, en expliquant les principaux types et examine certaines applications dans différents domaines. Dans le troisième chapitre, nous utilisons des automates cellulaires pour élaborer un nouveau modèle de comportement pour prédire la propagation de l’incendie, sur des bases elliptiques, dans des paysages homogènes et hétérogènes. La méthodologie proposée intègre les paramètres de la vitesse du vent, du carburant et de la topographie. Notre modèle développé est ensuite utilisé pour simuler les incendies de forêt qui ont balayé la forêt du village d'Aandqet, au nord du Liban. Les résultats de simulation obtenus sont comparés avec les résultats rapportés de l'incident réel et avec des simulations qu'on a iv effectuées sur le modèle de Karafyllidis et le modèle de Karafyllidis modifié par Gazmeh. Ces comparaisons ont prouvé l'ambiguë du modèle proposé. Dans cette thèse, la crise des feux de forêt a été étudiée et de nouveaux modèles ont été développés dans les deux phases: pré-feu et post-feu. Ces modèles peuvent être utilisés comme outils préventifs efficaces dans la gestion des incendies de forêtWildland fires are one of the most complex phenomena facing our societies. Lebanon, a part of Middle East, is losing its green forests dramatically mainly due to severe fires. This dissertation studies the phenomenon of forest fires. It proposes new models and methodologies to tackle the crisis of forest fires particularly in Lebanon and Mediterranean. It is divided into two main parts: New Approaches in Forest Fire Prediction and Forest Fire modeling. The first part is sub-divided into 3 chapters. First chapter presents an analytical study of the most widely used metrological models that can predict forest fires. In the second chapter we apply five data mining techniques methods: Neural Networks, Decision Tree, Fuzzy Logic, Linear Discriminate Analysis and Support Vector Machine. We aim to find the most accurate technique in forecasting forest fires. In the third chapter, we use different correlative data analysis techniques (Regression, Pearson, Spearman and Kendall-tau) to evaluate the correlation between fire occurrence and meteorological data (Temperature, Dew point, Soil temperature, Humidity, Precipitation and Wind speed). This allows to find the most influential parameters that affect the occurrence of fire, which lead us to develop a new Lebanese fire danger Index (LI). The proposed index is then validated using meteorological data for the years 2015-2016. The second part is sub-divided into 3 chapters. The first chapter reviews the fire behavior characteristics and its morphology; and focuses on the validity of mathematical and computer fire behavior models. The second chapter manifests the importance of cellular automata, explains the main types of cellular automata and reviews some applications in various domains. In the third chapter, we use cellular automata to develop a new behavior model for predicting the spread of fire, on elliptical basis, in both homogeneous and heterogeneous landscapes .The proposed methodology incorporates the parameters of wind speed, fuel and topography. The developed model is then used to simulate the wildfire that swept through the forest of Aandqet village, North Lebanon. Obtained simulation results are compared with reported results of the real incident and with simulations done on Karafyllidis model and Gazmeh-Modified Karafyllidis model. These comparisons have proven the outperformance of the proposed model. In this dissertation, the crisis of forest fires has been studied and new models have been developed in both phases: pre-fire and post-fire. These models can be used as efficient preventive tools in forest fire management
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Donner, Quentin. "Correction de l'atténuation et du rayonnement diffusé en tomographie d'émission à simples photons." Université Joseph Fourier (Grenoble), 1994. http://www.theses.fr/1994GRE10155.
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L'objectif de la tomographie d'émission à simples photons est d'établir une image fonctionnelle d'un organe. Pour ce faire, on administre au patient un radioélément qui se fixe dans l'organe, puis on calcule la distribution du radioélément à partir de mesures du rayonnement émis. Une proportion non négligeable de ce rayonnement interagit cependant dans la matière. L'objectif de ces travaux est de tenir compte de ces interactions afin de reconstruire plus précisément. Après avoir décrit les principales caractéristiques du système d'acquisition, nous nous consacrons a la reconstruction de la distribution d'émission à partir de projections atténuées, notamment quand la géométrie d'acquisition est conique. Plusieurs méthodes du type prédiction-correction sont fréquemment utilisées, mais leur convergence n'est pas établie. En fait, nous montrons théoriquement que la plus simple de ces méthodes diverge dans un cas particulier. La correction d'atténuation peut également être traitée par la méthode du gradient préconditionnée. Nous proposons plusieurs préconditionnements, qui conduisent à différents algorithmes de reconstruction. Ces algorithmes présentent de grandes analogies avec les algorithmes de prédiction-correction, mais ils ont l'avantage d'être convergents. Nous terminons ce chapitre en validant une méthode du type prédiction-correction, celle de Morozumi, sur données simulées et sur données expérimentales. Nous abordons ensuite le problème de la détermination de l'objet atténuant suivant deux approches. La première repose sur l'utilisation des mesures de rayonnement direct: on reconstruit l'émission une première fois sans corriger l'atténuation, puis on ajuste un ellipsoïde aux contours extérieurs de cette image. La seconde approche est basée sur l'utilisation des mesures du rayonnement diffuse: nous étudions la possibilité d'utiliser ces mesures pour établir une cartographie d'atténuation et nous mettons en évidence les difficultés liées a ce problème. Nous terminons en regardant comment la cartographie d'atténuation peut servir à corriger les effets du rayonnement diffuse. Nous proposons une méthode du type prédiction-correction, nous discutons sa convergence, puis nous la comparons a une méthode classique sur données expérimentales. .The aim of single photon emission tomography is to compute a functional picture of an organ. This is done by administering to the patient a radiopharmaceutical which is fixing in the organ. Then, one computes the distribution of the radiopharmaceutical from the measurement of the emitted gamma-rays. However, an important part of these gamma-rays are interacting with the matter inside the body. The aim of this work is to take these interactions into account so as to reconstruct more accurately. .
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Elazar, Yekutiel. "A mapping of the viscous flow behavior in a controlled diffusion compressor cascade using laser doppler velocimetry and preliminary evaluation of codes for the prediction of stall." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23296.
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Detailed measurements were made at M=0.25 and Re sub c = 700000 of the flow through a linear compressor cascade of controlled diffusion (CD) blading using a two-component argon-ion laser doppler velocimeter system. The measurements included mapping of the inviscid flow in the passage between two adjacent blades, boundary layer surveys, and wake surveys. Viscous flow phenomena such as a laminar separation region with reattachment on the suction surface, and laminar to turbulent transition on the pressure surface were resolved, and the viscous growth to the trailing edge was defined for three inlet angles from design incidence to near stall. Numerical calculations to predict the flow were carried out using a fully developed boundary layer code, a strongly interactive viscous inviscid code and a Navier Stokes code. It was shown that the common weakness of numerical predictors was in the modelling of transition and turbulence. The documented data can be used generally to calibrate compressor cascade analysis codes and thus enable reliable predictions of stall. Keywords: Laser doppler velocimeter measurements; Viscous cascade flow; Controlled diffusion blading; Code verification; Theses
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Lundberg, Emil. "Adding temporal plasticity to a self-organizing incremental neural network using temporal activity diffusion." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-180346.
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Vector Quantization (VQ) is a classic optimization problem and a simple approach to pattern recognition. Applications include lossy data compression, clustering and speech and speaker recognition. Although VQ has largely been replaced by time-aware techniques like Hidden Markov Models (HMMs) and Dynamic Time Warping (DTW) in some applications, such as speech and speaker recognition, VQ still retains some significance due to its much lower computational cost — especially for embedded systems. A recent study also demonstrates a multi-section VQ system which achieves performance rivaling that of DTW in an application to handwritten signature recognition, at a much lower computational cost. Adding sensitivity to temporal patterns to a VQ algorithm could help improve such results further. SOTPAR2 is such an extension of Neural Gas, an Artificial Neural Network algorithm for VQ. SOTPAR2 uses a conceptually simple approach, based on adding lateral connections between network nodes and creating “temporal activity” that diffuses through adjacent nodes. The activity in turn makes the nearest-neighbor classifier biased toward network nodes with high activity, and the SOTPAR2 authors report improvements over Neural Gas in an application to time series prediction. This report presents an investigation of how this same extension affects quantization and prediction performance of the self-organizing incremental neural network (SOINN) algorithm. SOINN is a VQ algorithm which automatically chooses a suitable codebook size and can also be used for clustering with arbitrary cluster shapes. This extension is found to not improve the performance of SOINN, in fact it makes performance worse in all experiments attempted. A discussion of this result is provided, along with a discussion of the impact of the algorithm parameters, and possible future work to improve the results is suggested.Vektorkvantisering (VQ; eng: Vector Quantization) är ett klassiskt problem och en enkel metod för mönsterigenkänning. Bland tillämpningar finns förstörande datakompression, klustring och igenkänning av tal och talare. Även om VQ i stort har ersatts av tidsmedvetna tekniker såsom dolda Markovmodeller (HMM, eng: Hidden Markov Models) och dynamisk tidskrökning (DTW, eng: Dynamic Time Warping) i vissa tillämpningar, som tal- och talarigenkänning, har VQ ännu viss relevans tack vare sin mycket lägre beräkningsmässiga kostnad — särskilt för exempelvis inbyggda system. En ny studie demonstrerar också ett VQ-system med flera sektioner som åstadkommer prestanda i klass med DTW i en tillämpning på igenkänning av handskrivna signaturer, men till en mycket lägre beräkningsmässig kostnad. Att dra nytta av temporala mönster i en VQ-algoritm skulle kunna hjälpa till att förbättra sådana resultat ytterligare. SOTPAR2 är en sådan utökning av Neural Gas, en artificiell neural nätverk-algorithm för VQ. SOTPAR2 använder en konceptuellt enkel idé, baserad på att lägga till sidleds anslutningar mellan nätverksnoder och skapa “temporal aktivitet” som diffunderar genom anslutna noder. Aktiviteten gör sedan så att närmaste-granne-klassificeraren föredrar noder med hög aktivitet, och författarna till SOTPAR2 rapporterar förbättrade resultat jämfört med Neural Gas i en tillämpning på förutsägning av en tidsserie. I denna rapport undersöks hur samma utökning påverkar kvantiserings- och förutsägningsprestanda hos algoritmen självorganiserande inkrementellt neuralt nätverk (SOINN, eng: self-organizing incremental neural network). SOINN är en VQ-algorithm som automatiskt väljer en lämplig kodboksstorlek och också kan användas för klustring med godtyckliga klusterformer. Experimentella resultat visar att denna utökning inte förbättrar prestandan hos SOINN, istället försämrades prestandan i alla experiment som genomfördes. Detta resultat diskuteras, liksom inverkan av parametervärden på prestandan, och möjligt framtida arbete för att förbättra resultaten föreslås.
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Moulton, Eric. "Methodological Considerations and Clinical Relevance of Diffusion Tensor Imaging in Acute Stroke Prognosis." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS249.
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Prédire la récupération après un Accident Vasculaire Cérébral (AVC) est un défi de la recherche. En plus de la valeur prédictive de la sévérité initiale d’un déficit, de l’âge et du volume de l’infarctus, les faisceaux de substance blanche jouent aussi un rôle pour chacune de ces fonctions. L’imagerie par tenseur de diffusion (DTI) peut quantifier l’intégrité de la substance blanche. Les travaux de cette thèse reposent sur une cohorte de patients thrombolysés ayant eu une IRM à 24 heures post-AVC. Les objectifs sont de (1) investiguer les stratégies de normalisation spatiale afin de mieux traiter les données, (2) établir quel paramètre du modèle DTI prédit le mieux la récupération globale, et (3) déterminer si le DTI peut fournir des biomarqueurs de la récupération de la motricité et du langage. Les résultats majeurs de cette thèse sont les suivants : (1) la normalisation basée sur les cartes de distribution d’orientation de fibres donnent des résultats similaires à la normalisation basée sur les cartes scalaires au stade aigu, mais fournit de meilleures corrélations anatomo-cliniques au stade subaigu-chronique, (2) la diffusivité axiale (AD) de la couronne rayonnante contribue à la prédiction de l’autonomie d’un patient et (3) l’AD du faisceau corticospinal et arqué constitue des biomarqueurs de la récupération de la motricité et de l’aphasie. Ces travaux mettent en avant l’usage de l’AD pour la quantification de la sévérité de l’ischémie aigüe dans la substance blanche. Ces marqueurs pourraient servir à informer les patients, à monitorer l’efficacité de thérapies neuroprotectrices au stade aigu ou bien à stratifier les patients pour des essais cliniquesPredicting motor, language, and global outcome after ischemic stroke is a major research concern. While initial impairment, age, and lesion volume have proven indicators of future outcome, the preservation of major white matter structures also play a role in these outcome domains. Diffusion tensor imaging (DTI) is sensitive to acute ischemic damage and can evaluate the integrity of important white matter bundles. Using a large cohort of patients who underwent a DTI protocol at 24 hours post-stroke and a clinical evaluation 3 months afterwards, the current thesis sought to (1) investigate spatial normalization strategies to optimally analyze imaging data, (2) establish which DTI parameter best predicts global outcome, and (3) determine if DTI can provide independent biomarkers of motor and language outcome. The major findings of the current thesis were: (1) fiber orientation distribution (FOD)-based spatial normalization performed similarly to scalar normalization for acute stroke data but yielded stronger anatomo-clinical correlations in subacute-chronic stroke patients, (2) axial diffusivity (AD) in the corona radiata highly contributes to the prediction of autonomy in patients, and (3) the AD of the corticospinal tract and arcuate fasciculus are independent markers of motor and aphasia outcome, respectively. These results support the use of AD for quantifying early brain damage in important white matter structures, such as the corona radiata, corticospinal tract, and arcuate fasciculus. These markers could be used for patient information, as surrogates of neuroprotective therapies at the hyperacute stage, or as stratification means for rehabilitative therapies
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Ho, Thi Kim Thoa. "Modélisation et analyse des réseaux complexes associées à des informations textuelles : les apports de la prétopologie, du topic modeling et de l’apprentissage automatique à l’étude de la dynamique des réseaux sociaux, la prédiction de liens et la diffusion des sujets." Thesis, Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLP047.
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L’objet de cette thèse porte sur le concept de réseau complexe associé à de l’information textuelle. Nous nous sommes intéressés à l’analyse de ces réseaux avec une perspective d’application aux réseaux sociaux. Notre première contribution a consisté à réaliser un modèle d’analyse pour un réseau social dynamique en utilisant l’approche de modélisation à base d’agents (agent based modeling ou ABM), modèle auteur-sujet du text-mining (« author-topic modeling » ou ATM), et en ayant recours à le cadre mathématique de la prétopologie pour représenter la proximité des sujets. Notre modélisation se nomme Textual-ABM. Notre démarche a été d’utiliser le modèle auteur-sujet pour estimer l’intérêt de l’utilisateur sur la base du contenu textuel et d’employer la prétopologie pour modéliser plusieurs relations et représenter un ensemble de voisinages plus élaboré qu’une simple relation. Notre deuxième contribution concerne la diffusion des informations sur un réseau social « hétérogène ». Nous proposons d’étendre le modèle de diffusion épidémique independant cascade model (IC) et le modèle de diffusion en cascade prétopologique que nous nommons respectivement Textual-Homo-IC et Textual-PCM. Pour Textual-Homo-IC, la probabilité d’infection est basée sur l’homophilie c’est-à-dire l’affiliation à des agents ressemblants, celle-ci est obtenue à partir du contenu textuel en utilisant le modèle de sujet (topic modeling). Pour Textual-PCM, une fonction d’adhérence (pseudo-closure function) avec différentes variantes d’association pour les relations qui la constitue est proposée pour réaliser un ensemble de voisinages plus complexe. En outre, nous proposons d’utiliser l’apprentissage supervisé pour prédire la diffusion d’un sujet avec une combinaison de facteurs intrinsèques ou externes. Notre troisième contribution concerne la présiction des relations entre co-auteurs avec l’ajout d’une nouvelle caractéristique topologique liés aux facteurs géographiques et fonctionnalités de contenu à l’aide du topic modeling. L’ensemble de ces travaux est accompagné d’une partie expérimentale et de la présentation des algorithmes développésThis thesis deals with the concept of complex network associated with textual information. We are interested in the analysis of these networks with a perspective of application to social networks. Our first contribution consisted in building an analysis model for a dynamic social network using the agent based modeling (ABM) approach, author-topic modeling (ATM), and using the mathematical framework of pretopology to represent the proximity of the subjects. Our modeling is called Textual-ABM. Our proposal has been to use author-topic modeling to estimate user interest based on text content and to use pretopology to model several relationships and to represent a set of neighborhoods that is more elaborate than a simple relationship. Our second contribution concerns the diffusion of information on a "heterogeneous" social network. We propose to extend the independent cascade epidemic diffusion model (IC) and the pretopological cascade diffusion model that we call Textual-Homo-IC and Textual-PCM respectively. For Textual-Homo-IC, the probability of infection is based on homophilia (resemblance of agents) which is obtained from the textual content using the topic modeling. For Textual-PCM, a pseudo-closure function with different strong levels is proposed to realize a more complex set of neighborhoods. In addition, we propose to use supervised learning to predict the diffusion of a topic with a combination of intrinsic or external factors. Our third contribution concerns the prediction of relationships between co-authors with the addition of a new topological feature related to geographical factors and content features using topic modelling. All this work was achieved by the design of specific algorithms and validated by experiments
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Francois, heude Alexandre. "Kinetic modeling of the polypropylene photothermal oxidation." Phd thesis, Ecole nationale supérieure d'arts et métiers - ENSAM, 2014. http://pastel.archives-ouvertes.fr/pastel-01069008.
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Developing numerical tools for polymer lifetime prediction constitutes a promising opportunity for shortening the duration of material certification procedures in the automotive industry without decreasing their reliability. This PhD thesis aims at modeling the photothermal oxidation of isotactic polypropylene (iPP), which is responsible for the alteration of both its mechanical and aspect properties. The adopted approach consists in coupling the kinetics of photo- and thermo-oxidation reactions with physical phenomena, such as oxygen transport and UV-light attenuation in the material thickness, in order to describe all the physico-chemical changes. Upper-scale properties, from which will be defined the end-of-life criteria, will be calculated afterwards by applying the suitable structure-property relationships. The main challenge was to extend the pre-existing kinetic model of thermal ageing to photothermal ageing by taking into account initiation reactions of photolysis. Heavy campaigns of ageing and characterization tests made on a reference iPP, as well as an exhaustive capitalization of literature data of other iPPs, have allowed elaborating a kinetic model of photothermal oxidation and to generalize it to the whole iPP family in large domains of oxygen partial pressure (from 0.2 to 50 bars), temperature (from 40 to 230°C) and UV-light exposure (variable intensities and light sources) describing both natural and accelerated ageing conditions. The experimental validation of the model has allowed substantiating the kinetic approach and showing its limitations, as well as highlighting some numerical issues. The model has been designed in order to be an upgradable numerical tool which will allow, at term, optimizing the representativeness of the ageing testing devices and the performance of commercial iPP formulations. All these theoretical and numerical developments are prone to be applied to the photothermal degradation of other types of polymer substrates, but also in other application fields of the macromolecular photochemistry such as UV-photopolymerization.Keywords: Polypropylene, photothermal oxidation, oxygen diffusion control, screen effect, kinetic modeling, lifetime prediction.
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Deshpande, Rutooj D. "UNDERSTANDING AND IMPROVING LITHIUM ION BATTERIES THROUGH MATHEMATICAL MODELING AND EXPERIMENTS." UKnowledge, 2011. http://uknowledge.uky.edu/cme_etds/4.
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There is an intense, worldwide effort to develop durable lithium ion batteries with high energy and power densities for a wide range of applications, including electric and hybrid electric vehicles. For improvement of battery technology understanding the capacity fading mechanism in batteries is of utmost importance. Novel electrode material and improved electrode designs are needed for high energy- high power batteries with less capacity fading. Furthermore, for applications such as automotive applications, precise cycle-life prediction of batteries is necessary.
One of the critical challenges in advancing lithium ion battery technologies is fracture and decrepitation of the electrodes as a result of lithium diffusion during charging and discharging operations. When lithium is inserted in either the positive or negative electrode, there is a volume change associated with insertion or de-insertion. Diffusion-induced stresses (DISs) can therefore cause the nucleation and growth of cracks, leading to mechanical degradation of the batteries. With different mathematical models we studied the behavior of diffusion induces stresses and effects of electrode shape, size, concentration dependent material properties, pre-existing cracks, phase transformations, operating conditions etc. on the diffusion induced stresses. Thus we develop tools to guide the design of the electrode material with better mechanical stability for durable batteries.
Along with mechanical degradation, chemical degradation of batteries also plays an important role in deciding battery cycle life. The instability of commonly employed electrolytes results in solid electrolyte interphase (SEI) formation. Although SEI formation contributes to irreversible capacity loss, the SEI layer is necessary, as it passivates the electrode-electrolyte interface from further solvent decomposition. SEI layer and diffusion induced stresses are inter-dependent and affect each-other. We study coupled chemical-mechanical degradation of electrode materials to understand the capacity fading of the battery with cycling. With the understanding of chemical and mechanical degradation, we develop a simple phenomenological model to predict battery life.
On the experimental part we come up with a novel concept of using liquid metal alloy as a self-healing battery electrode. We develop a method to prepare thin film liquid gallium electrode on a conductive substrate. This enabled us to perform a series of electrochemical and characterization experiments which certify that liquid electrode undergo liquid-solid-liquid transition and thus self-heals the cracks formed during de-insertion. Thus the mechanical degradation can be avoided. We also perform ab-initio calculations to understand the equilibrium potential of various lithium-gallium phases.
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Shain, Cory Adam. "Language, time, and the mind: Understanding human language processing using continuous-time deconvolutional regression." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1619002281033782.
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Cheng, Hua. "Hydrodynamic control of retention in heterogeneous aquifers and fractured rock." Doctoral thesis, Stockholm : KTH Architecture and the Built Environment, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-496.
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Trochmann, Jose Luiz Lino. "Simulação atomistica como ferramenta para investigação dos mecanismos de difusão : coeficientes de autodifusão de gases simples em matriz polimerica." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266175.
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Orientador: Sergio Persio RavagnaniTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica
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Resumo: Neste trabalho de tese foi realizado um estudo do potencial de predição de propriedades de transporte em matrizes poliméricas de poli - imidas, utilizando a simulação dinâmica molecular de gases simples como Oxigênio, Nitrogênio e Dióxido de Carbono. A propriedade de transporte de interesse prático, a permeabilidade de uma membrana polimérica a um dado penetrante, envolve a determinação de propriedades de ordem cinética e termodinâmica, respectivamente a determinação do coeficiente de difusão e da solubilidade deste penetrante na matriz polimérica. Atenção especial foi conferida à propriedade cinética, pela predição do coeficiente de autodifusão dos penetrantes. Num procedimento experimental clássico é de vital importância para significância das conclusões derivadas dos experimentos, o uso de amostras de membranas poliméricas adequadamente preparadas quanto à composição química, estrutura física e morfologia. Analogamente, quando se utiliza a simulação molecular para a predição de propriedades, tais como o coeficiente de autodifusão, também é de fundamental relevância para os resultados obtidos, a qualidade dos modelos moleculares das matrizes poliméricas, que serão usados como base. Assim para a preparação de modelos moleculares com o adequado empacotamento, um procedimento para a obtenção de modelos bem equilibrados foi desenvolvido neste trabalho. Os modelos moleculares desenvolvidos foram usados para a obtenção dos valores de massa específica em função da temperatura, e comparados aos valores experimentais disponíveis e quando necessário a, valores preditos por meio da expressão de massa específica em função da temperatura, acima e abaixo da temperatura de transição. A capacidade do modelo molecular desenvolvido em predizer a massa especifica e temperatura de transição vítrea foi usada como critério para a validação da adequação do empacotamento proposto para o referido modelo molecular da matriz polimérica. Os modelos validados de empacotamento, células amorfas, foram utilizados para o cálculo do coeficiente de autodifusão dos gases acima mencionados, através do da simulação dinâmica molecular. A comparação dos coeficientes de autodifusão obtidos das poli-imidas aromáticas e éster imidas, BAAF, 6FDA-ODA, PMDA-ODA e BA-20DA, para os gases O2, N2 e CO2, com os dados experimentais, permitiu concluir a adequação das células amorfas e do esquema de simulação dinâmica molecular para a predição do coeficiente de autodifusão.. A versão preditiva de Vrentas e Duda, baseada na teoria do volume livre, foi utilizada para a predição dos coeficientes de autodifusão da água e do etanol para as poli-imidas acima. , Estes valores, quando comparados com os valores obtidos através da simulação dinâmica molecular mostram a validade de ambas as teorias para a predição da cinética de difusão de penetrantes em matrizes poliméricas complexas
Abstract: In this thesis a study of the predictive potential of the molecular dynamic simulation was performed for transport properties of light gases in polyimide matrix. From de practical point of view permeability is the property of most interest, and involves kinetics as well as thermodynamics properties, diffusion coefficient and solubility of the penetrants molecule in the bulk polymeric matrix, this work will be focus in the former. As important as is in as experimental work, a well prepared polymeric membrane is essential for the significance of the draw conclusions. Therefore a special attention was take in the preparation of the bulk molecular polymeric model, the so called amorphous cell, in order to obtain well-equilibrated molecular packing models for the polyimide matrixes. The amorphous cells were prepared throughout thermodynamic transforms, using one or more of the statistical ensembles and cell specific volume obtained as a function of temperature, this data was compared against the experimental data available, and when necessary to data obtained via predictive methods. The molecular packing model ability to predict the glass transition temperature was used as criteria to validate de amorphous cell, to be used in the molecular dynamic' simulations allow the matrix to be locally flexible and coupled to the classic molecular dynamics simulation. The resulting self diffusion coefficients for the polyimide, BAAF, 6FDA-ODA, PMDAODA and BA-20DA for the gases O2, N2 e CO2 were compared to the experimental data. The lack of quality experimental diffusion data available for polyimide membranes for larger penetrants as water and ethanol, showed up as a good opportunity to assess the predictive capability of the molecular dynamic simulation for self diffusion coefficients, considering the relevant technological relevance of polyimide membranes for pervaporation process. The data of self diffusion coefficient produced by the predictive version of free-volume theory after Vrentas and Duda, was compared with the data produced via coupled molecular dynamic simulation for the water and ethanol penetrants, showing the relevance of both theories for the prediction of penetrants kinetic in complex polymeric matrixes
Doutorado
Ciencia e Tecnologia de Materiais
Doutor em Engenharia Química
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Flores, Livas José. "Computational and experimental studies of sp3-materials at high pressure." Thesis, Lyon 1, 2012. http://www.theses.fr/2012LYO10127.
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Nous présentons des études expérimentales et théoriques de disiliciures alcalino-terreux, le disilane (Si2H6) et du carbone à haute pression. Nous étudions les disiliciures et en particulier le cas d’une phase plane de BaSI2 qui a une structure hexagonale avec des liaisons sp3 entre les atomes de silicium. Cet environnement électronique conduit à un gaufrage de feuilles du silicium. Nous démontrons alors une amélioration de la température de transition supraconductrice de 6 à 8.9 K lorsque les couches de silicium s’aplanissent dans cette structure. Des calculs ab initio basés sur DFT ont guidé la recherche expérimentale et permettent d’expliquer comment les propriétés électroniques et des phonons sont fortement affectés par les fluctuations du flambage des plans de silicium. Nous avons aussi étudié les phases cristallines de disilane à très haute pression et une nouvelle phase métallique est proposé en utilisant les méthodes de prédiction de structure cristalline. Les températures de transition calculées donnant un supraconducteur autour de 20 K à 100 GPa. Ces valeurs sont significativement plus faibles comparées à celles avancées dans la littérature. Finalement, nous présentons des études de structures de carbone à haute pression à travers une recherche de structure systématique. Nous avons trouvé une nouvelle forme allotropique du carbone avec une symétrie Cmmm que nous appelons Z-carbone. Cette phase est prévue pour être plus stable que le graphite pour des pressions supérieures à 10 GPa. Des expériences et simulation de rayon-X et spectre Raman sugèrent l’existence de Z-carbone dans des micro-domaines de graphite sous pressionWe present experimental and theoretical studies of sp3 materials, alkaline-earth-metal (AEM) disilicides, disilane (Si2H6) and carbon at high pressure. First, we study the AEM disilicides and in particular the case of a layered phase of BaSi2 which has an hexagonal structure with sp3 bonding of the silicon atoms. This electronic environment leads to a natural corrugated Si-sheets. Extensive ab initio calculations based on DFT guided the experimental research and permit explain how electronic and phonon properties are strongly affected by changes in the buckling of the silicon plans. We demonstrate experimentally and theoretically an enhancement of superconducting transition temperatures from 6 to 8.9 K when silicon planes flatten out in this structure. Second, we investigated the crystal phases of disilane at the megabar range of pressure. A novel metallic phase of disilane is proposed by using crystal structure prediction methods. The calculated transition temperatures yielding a superconducting Tc of around 20 K at 100 GPa and decreasing to 13 K at 220 GPa. These values are significantly smaller than previously predicted Tc’s and put serious drawbacks in the possibility of high-Tc superconductivity based on silicon-hydrogen systems. Third, we studied the sp3-carbon structures at high pressure through a systematic structure search. We found a new allotrope of carbon with Cmmm symmetry which we refer to as Z-carbon. This phase is predicted to be more stable than graphite for pressures above 10 GPa and is formed by sp3-bonds. Experimental and simulated XRD, Raman spectra suggest the existence of Z-carbon in micro-domains of graphite under pressure
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Lin, Chieh. "Imagerie fonctionelle corps entier dans les hémopathies lymphoïdes." Thesis, Paris Est, 2009. http://www.theses.fr/2009PEST0053.
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Trois aspects principaux de l'imagerie fonctionnelle corps entier dans les hémopathies lymphoïdes ont été étudiés dans ma thèse. Nous avons d'abord démontré en étudiant 92 patients avec un lymphome B à grandes cellules que 14 patients (15%) considérés positifs sur l'analyse visuelle du FDG-TEP après deux cycles de chimiothérapie, auraient pu être reclassés comme des bons répondeurs si le pourcentage de réduction du SUVmax avait été mesuré. Dans un sous groupe de 80 patients, une deuxième étude a permis de montrer qu'après 4 cycles, l'analyse visuelle et l'analyse semi-quantitative SUV étaient équivalentes. Nous avons ensuite développé un protocole d'IRM fonctionnelle corps entier, utilisant une injection dynamique de Gadolinium et 5 stations d'acquisition. Cela a permis de mesurer les courbes signal-temps du rehaussement de la moelle osseuse et des lésions focales. Notre étude a permis d'optimiser un protocole d'imagerie dynamique corps entier après injection de Gadolinium, et de montrer que nous avions pu explorer avec succès 21 patients présentant un myélome multiple sous traitement, nous avons montré que cette nouvelle méthode d'IRM fonctionnelle corps entier avec injection de Gadolinium pouvait être utilisée pour évaluer la réponse du traitement. De plus, cette technique a aidé à détecter les lésions résiduelles actives de myélome après traitement alors qu'aucun signe clinique ou une immunoglobine monoclonale minime n'était présent. Le troisième aspect a été d'optimiser un protocole d'IRM fonctionnelle corps entier utilisant l'imagerie de diffusion avec asservissement respiratoire. Le but est de pouvoir mesurer le coefficient de diffusion apprent des lésions disséminées. L'étude pilote a été réalisée chez 15 patients avec un lymphome B à grandes cellules avant traitement. Nous avons aussi pu montrer les changements d'ADC après 4 cycles de chimiothérapie en considérant l'imagerie FDG-TEP/scanner comme imagerie de référenceThree components regarding whole-body functional imaging in lymphoid malignancies have been studies in this thesis. We first demonstrated retrospectively in a series of 92 patients with diffuse large B-cell lymphoma (DLBCL) that 14 patients (15%) considered as positive on visual analysis on FDG-PET after only 2 cycles of chemotherapy could have been correctly re-classified as good responders by measuring the percentage reduction of maximum standardized uptake value (SUVmax); in a subgroup of 80 patients, SUV-based assessment was equivalent to visual analysis at 4 cycles for patient outcome prediction. We secondly developed a whole-body 5-station dynamic contrast- enhanced MR protocol and time-signal intensity curves for the bone marrow and the focal lesions were successfully obtaines in 21 patients with plasma cell disorders included in the feasibility study; later in a pilot prospective study with 30 patients with multiple myeloma who received systemic therapy, we showed that this novel whole-body functional MR technique can be used to assess treatment response and helps to delect residual active disease after completion of therapy when clinically no or only minimum monoclonal protein can be identified. We thirdly optimized a whole-body diffusion-weighted MR protocol with respiratory gating in order to determine apparent diffusion coefficient (ADC) value on a whole-body scale. Pilot study was performed in 15 patients with DLBCL for both staging and response assessment at 4 cycles of chemotherapy, with FDG PET/CT as the standard of reference
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Liu, Qingfeng. "Multi-phase modelling of multi-species ionic migration in concrete." Thesis, University of Plymouth, 2014. http://hdl.handle.net/10026.1/3133.
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Chloride-induced corrosion of reinforcing steel in concrete is a worldwide problem. In order to predict how chlorides penetrate in concrete and how other ionic species in con-crete pore solution affect the penetration of chlorides, this thesis presents a numerical study on multi-phase modelling of ionic transport in concrete dominated by migration process. There are many advantages in rapid chloride migration test (RCM) method and numeri-cal approach. However, most of models in the literature predicting chloride diffusivity in concrete are diffusion models, which not consider the action of externally applied electric field. In view of this, the specific aim of this thesis is to develop a rational nu-merical migration model to simulate chloride migration tests. By using this model, the diffusion coefficient of chlorides in concrete will be efficiently predicted. Furthermore, other mechanisms of ionic transportation in composite materials can be scientifically in-vestigated in the meantime. In most existing work, researchers tend to use the assumption of electro-neutrality con-dition, which ensures that no external charge can be imported (Bockris and Reddy, 1998), to determine the electrostatic potential within concrete as well as considering a 1-D problem with only one phase structure and single species (i.e. the chlorides) for pre-dicting the ionic migration. In contrast, this thesis presents a number of sets of multi-phase migration models in more than one dimension and uses the Poisson’s equation for controlling the multi-species interactions. By solving both mass conservation and Pois-son’s equations, the distribution profiles of each ionic species and electrostatic potential at any required time are successfully obtained. Some significant factors, i.e. the influ-ence of dimensions, aggregates, interfacial transition zones (ITZs), cracks and binding effect have also been discussed in detail. The results reveal a series of important features which may not be seen from existing numerical models. For quantitative study, this thesis also provides the prediction method of chloride diffu-sivity not only by the traditional stationary diffusion models but also by the migration models presented in the thesis. The obtained results are compared with three proven analytical models, i.e., Maxwell’s model (Dormieux and Lemarchand, 2000), Brug-geman’s equation (Bruggeman’s, 1935) and the lower bound of the effective diffusion coefficient proposed by Li et al. (2012) as well as validated against experimental data sets of an accelerated chloride migration test (ACMT) brought by Yang and Su (2002).
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Elkin, Lauren S. "Predicting Diffusion of Contagious Diseases Using Social Media Big Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1408978084.
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Vasseur, Julien. "Fiabilité prévisionnelle de la tenue en service de composants mécaniques en présence d’amas de porosités détectés et caractérisés par contrôle non destructif ultrasonore." Thesis, Ecole nationale supérieure Mines-Télécom Lille Douai, 2020. http://www.theses.fr/2020MTLD0002.
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Ces travaux de thèse ont pour objectif de définir une méthodologie permettant d’estimer de manière réaliste la durée de vie d’une structure en alliage d’aluminium (aluminium 7075-T6) contenant des amas porosités. Le choix technique retenu vise à détecter et caractériser ces porosités au moyen de contrôles non destructifs (CND) par ultrasons et de corréler les images ultrasonores obtenues à des mesures de fatigue. Dans le cadre de nos travaux, ce problème est ramené à une étude 2D où l’amas de porosités est représenté par un ensemble de trous-génératrices usinés, dont les caractéristiques géométriques sont totalement contrôlables, contrairement à celles de la porosité réelle. En partie ultrasonore, un effort particulier est apporté dans la prise en compte des effets de diffusion multiple existant entre les défauts lors du contrôle. Une étude comparative du modèle d’imagerie ainsi développé est menée en confrontant nos simulations à d’autres simulations d’imagerie simplifiées (effectuées sur le logiciel CIVA) mais également à des mesures expérimentales. En partie fatigue, une résolution d’un cas très complexe s’avère nécessaire, puisqu’il implique des possibilités de multi-amorçage et de couplage local de modes de sollicitation. Ce problème de la propagation de la fissure en fatigue est résolu par la méthode G-Ө. Nous montrons l’efficacité de la méthodologie employée en comparant les résultats de durée de vie qu’elle permet de prédire et ceux trouvés expérimentalement par essais de fatigue. Enfin, afin de faire le lien entre le domaine du CND et celui de la mécanique de la rupture, nous présentons une méthode permettant d’estimer la tenue en fatigue d’une éprouvette au vu de son imagerie obtenue suite à son contrôle ultrasonore. Cette démarche permet ainsi de proposer une méthodologie originale couplant le contrôle ultrasonore et la fatigue, en mettant en place un chaînage entre les deux domaines pour la fiabilisation de la prédiction de la durée de vie des structures en fatigueThis work aims at defining a methodology for the lifetime estimation of aluminum alloy structures (aluminum 7075-T6) according to the properties of porosity clusters contained in the sample. We chose to use advanced ultrasonic imaging techniques to detect and characterize these porosities and then to correlate the ultrasonic images obtained with fatigue measurements. In the framework of our study, the problem is simplified with a 2D study where the cluster of porosities is represented as a set of side-drilled holes (SDH) whose geometric characteristics are fully controllable, unlike those of real porosity. A special effort is made to estimate the effects of multiple scattering due to wave interactions between defects. A comparative study of the imaging model thus developed is carried out by comparing our simulations including multiple scattering with other simplified simulation results (carried out on CIVA software) but also with experimental measurements. Concerning fatigue study, a phenomenological approach is suggested to take into account multi-cracks initiation and local multi-mode behaviour generated by the cluster of defects. Therefore, crack propagation is solved by a G-Ө finite element method for prediction of the fatigue lifetime of different samples with different cases of cluster of defects. Numerical and experimental results were compared showing that the suggested methodology gives realistic lifetimes despite of complexity of the studied cases. Finally, the overall originality of this thesis consists in making a direct link between NDT results and fatigue calculation. Thus, a method for estimating the fatigue life of a specimen based on inversed ultrasonic images of defects is suggested and applied on some studied cases
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Gambrell, Stefphanie Michelle. "Predicting the life cycle of rice varieties in Texas." Texas A&M University, 2004. http://hdl.handle.net/1969.1/3069.
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The Texas rice industry has undergone many changes over the course of the industryÂs existence. Recently, high costs of production and the structure of government payments have contributed to a decreasing trend in rice acreage planted in Texas. While Texas was once the top rice producer in the United States, it now ranks fifth. Despite the fact that Texas has one of the lowest levels of production among rice producing states, it currently maintains the highest per acre yields.
One of the major factors in maintaining superior yields is the development of high performance rice varieties and hybrids, which provide increased yields on fewer acres. Research institutions invest a great deal of time, effort, and money towards the development of new varieties every year. Each one of these varieties has a specific set of traits that are believed to be in high demand by producers and processors. However, during the developmental stages, scientists are uncertain as to how each new gerplasm will perform once it reaches the market.
This study develops a regression model, which includes competition and the characteristics of a specific variety, to estimate the life cycle of new varieties and hybrids. In addition, simulation techniques are utilized to incorporate risk into the life
cycle, providing a more robust prediction of the cumulative adoption and disadoption path.
Results indicate that the life cycle of new rice varieties is becoming shorter over time. Furthermore, the length of the life cycle is directly related to a new seedÂs performance, compared to other varieties on the market. Varieties that provide higher levels of performance, especially higher yields, tend to have a longer life cycle and achieve a larger market share, on average.
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Patton, Daya. "Predictive Relationships Between School Counselor Role Ambiguity, Role Diffusion, and Job Satisfaction." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6260.
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Lack of clarity about professional roles and responsibilities of school counselors has resulted in role ambiguity and role diffusion among this group of professionals. Role ambiguity and role diffusion contribute to job dissatisfaction. The purpose of this quantitative correlational study was to examine whether role ambiguity and role diffusion predicted school counselor job satisfaction after controlling for years of experience as a school counselor, and to examine whether role ambiguity, role diffusion, and job satisfaction differed for school counselors at the elementary, middle, and high school levels. The theoretical framework was role theory, which conceptualizes how job roles within organizations serve as boundaries between individuals and organizations. Survey data were collected from 86 school counselors at the elementary, middle, and high school levels. Results of linear regression analysis indicated that role ambiguity and role diffusion were significant predictors of job satisfaction after controlling for years of school counselor work experience. Results of discriminant analysis indicated no significant differences in school counselor role ambiguity, role diffusion, and job satisfaction based on school level. Findings may be used to advocate for aligning school counselors' duties and responsibilities with the training and education they receive, which may enable school counselors to be more satisfied in their jobs. The social change implication is that school counselors who are satisfied with their jobs could more effectively serve the children, schools, and communities in which they are assigned.
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Tepesch, Patrick David. "Atomistic modeling of ceramic materials : predicting crystal structures, thermodynamic properties, and diffusion behavior." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10936.
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Jiang, Jieyi Jiang. "Realistic Predictive Risk: The Role of Penalty and Covariate Diffusion in Model Selection." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1503072235693181.
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Mechelli, Luca [Verfasser]. "POD-based State-Constrained Economic Model Predictive Control for Convection-Diffusion Phenomena / Luca Mechelli." Konstanz : KOPS Universität Konstanz, 2019. http://d-nb.info/1200355075/34.
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Witty, Tricia. "An evaluation of molecular weight predictions in emulsion polymerization under conditions of diffusion limited chain transfer." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ59411.pdf.
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Wu, Ona. "Predictive models of tissue outcome in acute human cerebral ischemia using diffusion and perfusion weighted MRI." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8358.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references.
Diffusion (DWI) and perfusion weighted (PWI) magnetic resonance imaging (MRI) provide significant insight into acute stroke and can potentially be useful for clinical decision-making. In particular, current therapeutic decisions for acute human cerebral ischemia are typically based on time of symptom onset, limiting the number of patients treated. Imaging, however, offers insight into the physiologic integrity of brain tissue that is not attainable with time of symptom onset alone. This thesis extends existing imaging techniques for acute human stroke in order to improve identification of tissue at risk of infarction, thereby assisting clinical decision-making at the stage when intervention may be most effective. DWI and PWI have both been shown to identify infarcted tissue earlier than conventional stroke imaging. However, these techniques are limited in their existing implementations. DWI in most acute stroke settings has been restricted to isotropic imaging, measuring only mean diffusivity. In this thesis, DWI is extended to diffusion tensor imaging (DTI) with results demonstrating that DTI can detect ultrastructural changes in acute human stroke. PWI measures perfusion status by tracking the first pass of a bolus of contrast agent. In this dissertation, using numerical simulations, delay in contrast agent arrival is found to result in biased estimates of perfusion indices. A deconvolution technique using a block-circulant matrix is therefore proposed to compensate for delayed arrival, and its performance is compared to non-block circulant techniques in simulations as well as in clinically acquired human data sets.
(cont.) The results show that decoupling delay-associated effects reduces bias in tissue perfusion estimates. Algorithms combining DWI and PWI information are also evaluated to determine whether they predict tissue outcome in acute stroke better than models using only subsets of these parameters. Results show that algorithms combining DWI and PWI on a voxel-by-voxel basis predict tissue that infarct with higher specificity and sensitivity than algorithms using DWI or PWI individually. These combination algorithms are then used to investigate the efficacy of a novel therapeutic agent by evaluating the performance of the model as a function of treatment dose. Findings suggest that predictive models allow evaluation of novel therapies using smaller sample sizes than traditional endpoints. The results of this dissertation demonstrate that imaging can be used to identify tissue at risk of infarction, which may aid diagnosis and prognosis by providing clinicians unique insight into the underlying pathophysiology of stroke.
by Ona Wu.
Ph.D.
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Heesen, Bernd. "Diffusion of innovations : factors predicting the use of e-learning at institutions of higher education in Germany." Berlin dissertation.de, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2833665&prov=M&dokv̲ar=1&doke̲xt=htm.
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Heesen, Bernd. "Diffusion of innovations factors predicting the use of e-learning at institutions of higher education in Germany." Berlin dissertation.de, 2004. http://deposit.d-nb.de/cgi-bin/dokserv?id=2833665&prov=M&dok_var=1&dok_ext=htm.
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Uznanski, Przemyslaw. "Large scale platform : Instantiable models and algorithmic design of communication schemes." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00878837.
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The increasing popularity of Internet bandwidth-intensive applications prompts us to consider followingproblem: How to compute efficient collective communication schemes on large-scale platform?The issue of designing a collective communication in the context of a large scale distributed networkis a difficult and a multi-level problem. A lot of solutions have been extensively studied andproposed. But a new, comprehensive and systematic approach is required, that combines networkmodels and algorithmic design of solutions.In this work we advocate the use of models that are able to capture real-life network behavior,but also are simple enough that a mathematical analysis of their properties and the design of optimalalgorithms is achievable.First, we consider the problem of the measuring available bandwidth for a given point-topointconnection. We discuss how to obtain reliable datasets of bandwidth measurements usingPlanetLab platform, and we provide our own datasets together with the distributed software usedto obtain it. While those datasets are not a part of our model per se, they are necessary whenevaluating the performance of various network algorithms. Such datasets are common for latencyrelatedproblems, but very rare when dealing with bandwidth-related ones.Then, we advocate for a model that tries to accurately capture the capabilities of a network,named LastMile model. This model assumes that essentially the congestion happens at the edgesconnecting machines to the wide Internet. It has a natural consequence in a bandwidth predictionalgorithm based on this model. Using datasets described earlier, we prove that this algorithm is ableto predict with an accuracy comparable to best known network prediction algorithm (DistributedMatrix Factorization) available bandwidth between two given nodes. While we were unable toimprove upon DMF algorithm in the field of point-to-point prediction, we show that our algorithmhas a clear advantage coming from its simplicity, i.e. it naturally extends to the network predictionsunder congestion scenario (multiple connections sharing a bandwidth over a single link). We areactually able to show, using PlanetLab datasets, that LastMile prediction is better in such scenarios.In the third chapter, we propose new algorithms for solving the large scale broadcast problem.We assume that the network is modeled by the LastMile model. We show that under thisassumption, we are able to provide algorithms with provable, strong approximation ratios. Takingadvantage of the simplicity and elasticity of the model, we can even extend it, so that it captures theidea of connectivity artifacts, in our case firewalls preventing some nodes to communicate directlybetween each other. In the extended case we are also able to provide approximation algorithmswith provable performance.The chapters 1 to 3 form three successful steps of our program to develop from scratch amathematical network communication model, prove it experimentally, and show that it can beapplied to develop algorithms solving hard problems related to design of communication schemesin networks.In the chapter 4 we show how under different network cost models, using some simplifyingassumptions on the structure of network and queries, one can design very efficient communicationschemes using simple combinatorial techniques. This work is complementary to the previous chapter in the sense that previously when designing communication schemes, we assumed atomicityof connections, i.e. that we have no control over routing of simple connections. In chapter 4 weshow how to solve the problem of an efficient routing of network request, given that we know thetopology of the network. It shows the importance of instantiating the parameters and the structureof the network in the context of designing efficient communication schemes.
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Zhou, Xueqing. "Predicting Solute Transport in Natural Streams - A Stochastic Approach." PDXScholar, 1994. https://pdxscholar.library.pdx.edu/open_access_etds/5057.
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The existing theories for predicting longitudinal dispersion in straight open channels have long been recognized as inadequate when applied to natural rivers. These theories tend to grossly underestimate dispersion in real streams since an important mixing mechanism due to nonuniform river cross-section variations is not explicitly taken into account. Recognizing the important role of stream irregularities on solute transport and the analytical difficulties of classical deterministic analysis, we develop a stochastic approach for analyzing solute transport in natural streams. Variations in river width and bed elevation are conveniently represented as one-dimensional random fields, characterized by their autocorrelation functions. Advection and dispersion due to the combined effect of turbulent diffusion and nonuniform flow are described by the stochastic solute transport equation. When boundary variations are small and statistically homogeneous, a stochastic spectral technique is used to obtain closed-form stochastic solutions. In particular, closed-form expressions are obtained for effective mean solute transport velocity and effective dispersion coefficient reflecting mixing due to flow variations both within the river cross-section and in the streamwise direction. The results show that the mean behavior of solute transport in a statistically irregular stream can be described as a gradient dispersion process. The effective mean transport velocity in natural rivers is smaller than that in a corresponding uniform channel, and the effective longitudinal dispersion coefficient in natural rivers can be considerably greater than that of uniform open channels. The discrepancy between uniform channels and natural rivers increases rapidly as the variances of river width and bed elevation increase, especially when the mean flow Froude number is high.
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Hoang, Thi Bich Ngoc. "Information diffusion, information and knowledge extraction from social networks." Thesis, Toulouse 2, 2018. http://www.theses.fr/2018TOU20078.
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La popularité des réseaux sociaux a rapidement augmenté au cours de la dernière décennie. Selon Statista, environ 2 milliards d'utilisateurs utiliseront les réseaux sociaux d'ici janvier 2018 et ce nombre devrait encore augmenter au cours des prochaines années. Tout en gardant comme objectif principal de connecter le monde, les réseaux sociaux jouent également un rôle majeur dans la connexion des commerçants avec les clients, les célébrités avec leurs fans, les personnes ayant besoin d'aide avec les personnes désireuses d'aider, etc.. Le succès de ces réseaux repose principalement sur l'information véhiculée ainsi que sur la capacité de diffusion des messages dans les réseaux sociaux. Notre recherche vise à modéliser la diffusion des messages ainsi qu'à extraire et à représenter l'information des messages dans les réseaux sociaux. Nous introduisons d'abord une approche de prédiction de la diffusion de l'information dans les réseaux sociaux. Plus précisément, nous prédisons si un tweet va être re-tweeté ou non ainsi que son niveau de diffusion. Notre modèle se base sur trois types de caractéristiques: basées sur l'utilisateur, sur le temps et sur le contenu. Nous avons évalué notre modèle sur différentes collections correspondant à une douzaine de millions de tweets. Nous avons montré que notre modèle améliore significativement la F-mesure par rapport à l'état de l'art, à la fois pour prédire si un tweet va être re-tweeté et pour prédire le niveau de diffusion. La deuxième contribution de cette thèse est de fournir une approche pour extraire des informations dans les microblogs. Plusieurs informations importantes sont incluses dans un message relatif à un événement, telles que la localisation, l'heure et les entités associées. Nous nous concentrons sur l'extraction de la localisation qui est un élément primordial pour plusieurs applications, notamment les applications géospatiales et les applications liées aux événements. Nous proposons plusieurs combinaisons de méthodes existantes d'extraction de localisation dans des tweets en ciblant des applications soit orientées rappel soit orientées précision. Nous présentons également un modèle pour prédire si un tweet contient une référence à un lieu ou non. Nous montrons que nous améliorons significativement la précision des outils d'extraction de lieux lorsqu'ils se focalisent sur les tweets que nous prédisons contenir un lieu. Notre dernière contribution présente une base de connaissances permettant de mieux représenter l'information d'un ensemble de tweets liés à des événements. Nous combinons une collection de tweets de festivals avec d'autres ressources issues d'Internet pour construire une ontologie de domaine. Notre objectif est d'apporter aux utilisateurs une image complète des événements référencés au sein de cette collectionThe popularity of online social networks has rapidly increased over the last decade. According to Statista, approximated 2 billion users used social networks in January 2018 and this number is still expected to grow in the next years. While serving its primary purpose of connecting people, social networks also play a major role in successfully connecting marketers with customers, famous people with their supporters, need-help people with willing-help people. The success of online social networks mainly relies on the information the messages carry as well as the spread speed in social networks. Our research aims at modeling the message diffusion, extracting and representing information and knowledge from messages on social networks. Our first contribution is a model to predict the diffusion of information on social networks. More precisely, we predict whether a tweet is going to be diffused or not and the level of the diffusion. Our model is based on three types of features: user-based, time-based and content-based features. Being evaluated on various collections corresponding to dozen millions of tweets, our model significantly improves the effectiveness (F-measure) compared to the state-of-the-art, both when predicting if a tweet is going to be retweeted or not, and when predicting the level of retweet. The second contribution of this thesis is to provide an approach to extract information from microblogs. While several pieces of important information are included in a message about an event such as location, time, related entities, we focus on location which is vital for several applications, especially geo-spatial applications and applications linked to events. We proposed different combinations of various existing methods to extract locations in tweets targeting either recall-oriented or precision-oriented applications. We also defined a model to predict whether a tweet contains a location or not. We showed that the precision of location extraction tools on the tweets we predict to contain a location is significantly improved as compared when extracted from all the tweets.Our last contribution presents a knowledge base that better represents information from a set of tweets on events. We combined a tweet collection with other Internet resources to build a domain ontology. The knowledge base aims at bringing users a complete picture of events referenced in the tweet collection (we considered the CLEF 2016 festival tweet collection)
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Nguyen, Cu Ngoc. "Stochastic differential equations with long-memory input." Thesis, Queensland University of Technology, 2001.
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Malmaeus, Jan Mikael. "Predictive Modeling of Lake Eutrophication." Doctoral thesis, Uppsala University, Department of Earth Sciences, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4625.
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This thesis presents predictive models for important variables concerning eutrophication effects in lakes. The keystone is a dynamic phosphorus model based on ordinary differential equations. By calculating mass fluxes of phosphorus into, within and out from a lake, the concentrations of different forms of phosphorus in different compartments of the lake are estimated.
The dynamic phosphorus model is critically tested and several improvements are presented, including two new compartments for colloidal phosphorus, a sub-model for suspended particulate matter (SPM) and new algorithms for lake outflow, water mixing, diffusion, water content and organic content of accumulation sediments are implemented. Predictions with the new version show good agreement against empirical data in five tested lakes.
The sub-model for SPM uses the same driving variables as the basic phosphorus model, so the inclusion of this model as a sub-model does not require any additional variables. The model for SPM may also be used as a separate model giving monthly predictions of suspended particulate matter in two water compartments and one compartment with SPM available for resuspension in ET-sediments.
Empirical data from Lake Erken (Sweden) and Lake Balaton (Hungary) are used to evaluate the variability in settling velocity of SPM. It is found that the variability is substantial and may be accounted for by using a dimensionless moderator for SPM concentration. Empirical data from accumulation area sediments in Lake Erken are used to develop a model for the dynamics of phosphorus sedimentation, burial and diffusion in the sediments. The model is shown to provide reasonable monthly predictions of four functional forms of phosphorus at different sediment depths.
Simulations with the lake phosphorus model using two different climate scenarios indicate that lakes may respond very differently to climate change depending on their physical character. Lake Erken, with a water retention time of 7 years, appears to be much more sensitive than two basins of Lake Mälaren (Sweden) with substantially shorter retention times. The implication would be that in eutrophic lakes with long water retention times, eutrophication problems may become serious if the future becomes warmer. This will be important in contexts of lake management when remedial measures against lake eutrophication have to be taken.
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Guille, Adrien. "Diffusion de l’information dans les médias sociaux : modélisation et analyse." Thesis, Lyon 2, 2014. http://www.theses.fr/2014LYO22015/document.
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Les médias sociaux ont largement modifié la manière dont nous produisons, diffusons et consommons l'information et sont de fait devenus des vecteurs d'information importants. L’objectif de cette thèse est d’aider à la compréhension du phénomène de diffusion de l’information dans les médias sociaux, en fournissant des moyens d’analyse et de modélisation.Premièrement, nous proposons MABED, une méthode statistique pour détecter automatiquement les évènements importants qui suscitent l'intérêt des utilisateurs des médias sociaux à partir du flux de messages qu'ils publient, dont l'originalité est d'exploiter la fréquence des interactions sociales entre utilisateurs, en plus du contenu textuel des messages. Cette méthode diffère par ailleurs de celles existantes en ce qu'elle estime dynamiquement la durée de chaque évènement, plutôt que de supposer une durée commune et fixée à l'avance pour tous les évènements. Deuxièmement, nous proposons T-BASIC, un modèle probabiliste basé sur la structure de réseau sous-jacente aux médias sociaux pour prédire la diffusion de l'information, plus précisément l'évolution du volume d'utilisateurs relayant une information donnée au fil du temps. Contrairement aux modèles similaires également basés sur la structure du réseau, la probabilité qu'une information donnée se diffuse entre deux utilisateurs n'est pas constante mais dépendante du temps. Nous décrivons aussi une procédure pour l'inférence des paramètres latents du modèle, dont l'originalité est de formuler les paramètres comme des fonctions de caractéristiques observables des utilisateurs. Troisièmement, nous proposons SONDY, un logiciel libre et extensible implémentant des méthodes tirées de la littérature pour la fouille et l'analyse des données issues des médias sociaux. Le logiciel manipule deux types de données : les messages publiés par les utilisateurs, et la structure du réseau social interconnectant ces derniers. Contrairement aux logiciels académiques existants qui se concentrent soit sur l'analyse des messages, soit sur l'analyse du réseau, SONDY permet d'analyser ces deux types de données conjointement en permettant l'analyse de l'influence par rapport aux évènements détectés. Les expérimentations menées à l'aide de divers jeux de données collectés sur le média social Twitter démontrent la pertinence de nos propositions et mettent en lumière des propriétés qui nous aident à mieux comprendre les mécanismes régissant la diffusion de l'information. Premièrement, en comparant les performances de MABED avec celles de méthodes récentes tirées de la littérature, nous montrons que la prise en compte des interactions sociales entre utilisateurs conduit à une détection plus précise des évènements importants, avec une robustesse accrue en présence de contenu bruité. Nous montrons également que MABED facilite l'interprétation des évènements détectés en fournissant des descriptions claires et précises, tant sur le plan sémantique que temporel. Deuxièmement, nous montrons la validité de la procédure proposée pour estimer les probabilités de diffusion sur lesquelles repose le modèle T-BASIC, en illustrant le pouvoir prédictif des caractéristiques des utilisateurs sélectionnées et en comparant les performances de la méthode d'estimation proposée avec celles de méthodes tirées de la littérature. Nous montrons aussi l'intérêt d'avoir des probabilités non constantes, ce qui permet de prendre en compte dans T-BASIC la fluctuation du niveau de réceptivité des utilisateurs des médias sociaux au fil du temps. Enfin, nous montrons comment, et dans quelle mesure, les caractéristiques sociales, thématiques et temporelles des utilisateurs affectent la diffusion de l'information. Troisièmement, nous illustrons à l'aide de divers scénarios l'utilité du logiciel SONDY, autant pour des non-experts, grâce à son interface utilisateur avancée et des visualisations adaptées, que pour des chercheurs du domaine, grâce à son interface de programmationSocial media have greatly modified the way we produce, diffuse and consume information, and have become powerful information vectors. The goal of this thesis is to help in the understanding of the information diffusion phenomenon in social media by providing means of modeling and analysis.First, we propose MABED (Mention-Anomaly-Based Event Detection), a statistical method for automatically detecting events that most interest social media users from the stream of messages they publish. In contrast with existing methods, it doesn't only focus on the textual content of messages but also leverages the frequency of social interactions that occur between users. MABED also differs from the literature in that it dynamically estimates the period of time during which each event is discussed rather than assuming a predefined fixed duration for all events. Secondly, we propose T-BASIC (Time-Based ASynchronous Independent Cascades), a probabilistic model based on the network structure underlying social media for predicting information diffusion, more specifically the evolution of the number of users that relay a given piece of information through time. In contrast with similar models that are also based on the network structure, the probability that a piece of information propagate from one user to another isn't fixed but depends on time. We also describe a procedure for inferring the latent parameters of that model, which we formulate as functions of observable characteristics of social media users. Thirdly, we propose SONDY (SOcial Network DYnamics), a free and extensible software that implements state-of-the-art methods for mining data generated by social media, i.e. the messages published by users and the structure of the social network that interconnects them. As opposed to existing academic tools that either focus on analyzing messages or analyzing the network, SONDY permits the joint analysis of these two types of data through the analysis of influence with respect to each detected event.The experiments, conducted on data collected on Twitter, demonstrate the relevance of our proposals and shed light on some properties that give us a better understanding of the mechanisms underlying information diffusion. First, we compare the performance of MABED against those of methods from the literature and find that taking into account the frequency of social interactions between users leads to more accurate event detection and improved robustness in presence of noisy content. We also show that MABED helps with the interpretation of detected events by providing clearer textual description and more precise temporal descriptions. Secondly, we demonstrate the relevancy of the procedure we propose for estimating the pairwise diffusion probabilities on which T-BASIC relies. For that, we illustrate the predictive power of users' characteristics, and compare the performance of the method we propose to estimate the diffusion probabilities against those of state-of-the-art methods. We show the importance of having non-constant diffusion probabilities, which allows incorporating the variation of users' level of receptivity through time into T-BASIC. We also study how -- and in which proportion -- the social, topical and temporal characteristics of users impact information diffusion. Thirdly, we illustrate with various scenarios the usefulness of SONDY, both for non-experts -- thanks to its advanced user interface and adapted visualizations -- and for researchers -- thanks to its application programming interface