In this thesis, we consider the problem of capturing finite-representability between Banach spaces using the tools of continuous model theory. We introduce predicates and additional sorts to capture finite-representability and show that these can be used to expand the language of Banach spaces. We then show that the class of infinite-dimensional Banach spaces expanded with this additional structure forms an elementary class K_G , and conclude that the theory T_G of K_G is interpretable in T^{eq} , where T is the theory of infinite-dimensional Banach spaces. Finally, we show that existential equivalence in a reduct of the language implies finite-representability. Relevant background on continuous model theory and Banach space theory is provided. / Thesis / Master of Science (MSc)

There has been confusion in choosing a proper survival model between two popular survival models of discrete and continuous survival analysis. This study aimed to provide empirical outcomes of two survival models in educational contexts and suggest a guideline for researchers who should adopt a suitable survival model. For the model specification, the study paid attention to three factors of time metrics, censoring proportions, and sample sizes. To arrive at comprehensive understanding of the three factors, the study investigated the separate and combined effect of these factors. Furthermore, to understand the interaction mechanism of those factors, this study examined the role of the factors to determine hazard rates which have been known to cause the discrepancies between discrete and continuous survival models. To provide empirical evidence from different combinations of the factors in the use of survival analysis, this study built a series of discrete and continuous survival models using secondary data and simulated data. In the first study, using empirical data from the National Longitudinal Survey of Youth 1997 (NLSY97), this study compared analyses results from the two models having different sizes of time metrics. In the second study, by having various specifications with combination of two other factors of censoring proportions and sample sizes, this study simulated datasets to build two models and compared the analysis results. The major finding of the study is that discrete models are recommended in the conditions of large units of time metrics, low censoring proportion, or small sample sizes. Particularly, discrete model produced better outcomes for conditions with low censoring proportion (20%) and small number (i.e., four) of large time metrics (i.e., year) regardless of sample sizes. Close examination of those conditions of time metrics, censoring proportion, and sample sizes showed that the conditions resulted into high hazards (i.e., 0.20). In conclusion, to determine a proper model, it is recommended to examine hazards of each of the time units with the specific factors of time metrics, censoring proportion and sample sizes. / Ph. D.

Recent developments in instrumentation, communication and software have enabled the integration of real-time data into the decision-making process of hydrocarbon production. Applications of real-time data integration in drilling operations and horizontal-well lateral placement are becoming industry common practice. In reservoir management, the use of real-time data has been shown to be advantageous in tasks such as improving smart-well performance and in pressure-maintenance programs. Such capabilities allow for a paradigm change in which reservoir management can be looked at as a strategy that enables a semi-continuous process of model updates and decision optimizations instead of being periodic or reactive. This is referred to as closed-loop reservoir management (CLRM). Due to the complexity of the dynamic physical processes, large sizes, and huge uncertainties associated with reservoir description, continuous model updating is a large-scale problem with a highly dimensional parameter space and high computational costs. The need for an algorithm that is both feasible for practical applications and capable of generating reliable estimates of reservoir uncertainty is a key element in CLRM. This thesis investigates the validity of Markov Chain Monte Carlo (MCMC) sampling used in a Bayesian framework as an uncertainty quantification and model-updating tool suitable for real-time applications. A 3-phase, dual-porosity, dual-permeability reservoir model is used in a synthetic experiment. Continuous probability density functions of cumulative oil production for two cases with different model updating frequencies and reservoir maturity levels are generated and compared to a case with a known geology, i.e., truth case. Results show continuously narrowing ranges for cumulative oil production, with mean values approaching the truth case as model updating advances and the reservoir becomes more mature. To deal with MCMC sampling sensitivity to increasing numbers of observed measurements, as in the case of real-time applications, a new formulation of the likelihood function is proposed. Changing the likelihood function significantly improved chain convergence, chain mixing and forecast uncertainty quantification. Further, methods to validate the sampling quality and to judge the prior model for the MCMC process in real applications are advised.

京都大学 / 0048 / 新制・課程博士 / 博士(医科学) / 甲第21024号 / 医科博第85号 / 新制||医科||6(附属図書館) / 京都大学大学院医学研究科医科学専攻 / (主査)教授 川上 浩司, 教授 黒田 知宏, 教授 森田 智視 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Understanding how car travel and ownership respond to income and fuel prices, and how that response varies between households is crucial for car use policies and forecasts. This thesis, consisting of two papers, aims to investigate this by estimating the intemporal income and fuel price elasticities of car use using micro registry panel data on all Swedish households from 1998 to 2018. In Paper I, the income and fuel price elasticities of vehicle kilometres travelled (VKT) is estimated for all Swedish households using a linear fixed effects model. In order to investigate how different groups respond, the elasticities are estimated by income group and municipality type. The effect of income and fuel prices on VKT is largest in the middle of the income distribution but is relatively stable across municipality types. The effect of fuel prices on VKT is largest in densely populated municipalities compared to rural municipalities. Moreover, it is shown that the income elasticity is underestimated if income variable is misspecified. Paper II utilises a discrete-continuous model accounting for the effect of income and fuel prices on car ownership. It is shown that income impacts car ownership and VKT conditional on car ownership of similar magnitude, while fuel prices primarily impact VKT conditional on car ownership. Furthermore, we also estimate the model on six partially overlapping sample periods and find that the income elasticity has decreased over time, while the absolute fuel price elasticity increased up until the early 2010s and decreased thereafter. / <p>2022-10-13: ISBN (PDF) has been added in the E-version.</p>

Understanding how car travel and ownership respond to income and fuel prices, and how that response varies between households is crucial for car use policies and forecasts. This thesis, consisting of two papers, aims to investigate this by estimating the intemporal income and fuel price elasticities of car use using micro registry panel data on all Swedish households from 1998 to 2018. In Paper I, the income and fuel price elasticities of vehicle kilometres travelled (VKT) is estimated for all Swedish households using a linear fixed effects model. In order to investigate how different groups respond, the elasticities are estimated by income group and municipality type. The effect of income and fuel prices on VKT is largest in the middle of the income distribution but is relatively stable across municipality types. The effect of fuel prices on VKT is largest in densely populated municipalities compared to rural municipalities. Moreover, it is shown that the income elasticity is underestimated if income variable is misspecified. Paper II utilises a discrete-continuous model accounting for the effect of income and fuel prices on car ownership. It is shown that income impacts car ownership and VKT conditional on car ownership of similar magnitude, while fuel prices primarily impact VKT conditional on car ownership. Furthermore, we also estimate the model on six partially overlapping sample periods and find that the income elasticity has decreased over time, while the absolute fuel price elasticity increased up until the early 2010s and decreased thereafter.

<p>In this thesis we prove a strong conceptual completeness result for first-order continuous logic. Strong conceptual completeness was proved in 1987 by Michael Makkai for classical first-order logic, and states that it is possible to recover a first-order theory T by looking at functors originating from the category Mod(T) of its models. </p> <p> We then give a brief account of simple theories in continuous logic, and give a proof that the characterization of simple theories using dividing holds in continuous structures. These results are a specialization of well established results for thick cats which appear in [Ben03b] and in [Ben03a].</p> <p> Finally, we turn to the study of non-archimedean Banach spaces over non-trivially valued fields. We give a natural language and axioms to describe them, and show that they admit quantifier elimination, and are N0-stable. We also show that the theory of non-archimedean Banach spaces has only one N 1-saturated model in any cardinality. </p> / Thesis / Doctor of Philosophy (PhD)

No description available.

Understanding joint and causal relationships among multiple endogenous variables has been of much interest to researchers in the field of activity and travel behavior modeling. Structural equation models have been widely developed for modeling and analyzing the causal relationships among travel time, activity duration, car ownership, trip frequency and activity frequency. In the model, travel time and activity duration are treated as continuous variables, while car ownership, trip frequency and activity frequency as ordered discrete variables. However, many endogenous variables of interest in travel behavior are not continuous or ordered discrete but unordered discrete in nature, such as mode choice, destination choice, trip chaining pattern and time-of-day choice (it can be classified into a few categories such as AM peak, midday, PM peak and off-peak). A modeling methodology with involvement of unordered discrete variables is highly desired for better understanding the causal relationships among these variables. Under this background, the proposed dissertation study will be dedicated into seeking an appropriate modeling methodology which aids in identifying the causal relationships among activity and travel variables including unordered discrete variables. In this dissertation, the proposed modeling methodologies are applied for modeling the causal relationship between three pairs of endogenous variables: trip chaining pattern vs. mode choice, activity timing vs. duration and trip departure time vs.mode choice. The data used for modeling analysis is extracted from Swiss Travel Microcensus 2000. Such models provide us with rigorous criteria in selecting a reasonable application sequence of sub-models in the activity-based travel demand model system.

Fenômenos multifásicos são frequentemente observados na natureza, tais como nas gotas de chuva ou neve no ar, nos vulcões e tempestades de areia, e em diversas outras situações. Na solução desses problemas que envolvem escoamentos gás-sólidos e granulares são frequentemente utilizadas duas abordagens: a contínua (formulação Euleriana-Euleriana) e a discreta (formulação Euleriana-Lagrangiana). Na abordagem discreta pode-se utilizar dois modelos para descrever o contato entre as partículas: o modelo de esfera rígida e o modelo de esfera suave. Neste trabalho é realizado um estudo detalhado dos modelos de contato, com foco na modelagem de esfera suave, que é baseada em um sistema dinâmico mola-massa-amortecedor. Por meio desse estudo, com a finalidade de aprimorar o modelo de contato não-linear, são propostas duas relações para o mecanismo de contato de partículas. Essas relações são fundamentadas em um modelo dinâmico, com não-linearidades nas partes conservativas e dissipativas, não apresentando descontinuidades entre as acelerações do início e do fim do contato. A metodologia de desenvolvimento da presente pesquisa está dividida em três partes: pesquisa bibliográfica dos modelos de contato; estudo analítico e numérico desses modelos e testes de problemas com a realização de experimentos numéricos, utilizando o código computacional MFIX (Multiphase Flow with Interphase eXchange). As novas aproximações propostas neste trabalho são analisadas e aplicadas em três diferentes problemas: de dinâmica, escoamento gás-sólido e escoamento granular. Os resultados obtidos utilizando as relações são comparados com dados disponíveis na literatura, mostrando-se adequados para os casos investigados neste trabalho. / Multiphase flow are frequently observed in nature, such as rain drops in air or snowfalls, volcanoes and sandstorms, and several other situations. For solving these problems which involve gas-solid and granular flows are often used two models: the continuous model (Eulerian-Eulerian formulation) and the discrete model (Eulerian-Lagrangian formulation). There are two main contact models used in DEM, the hard-sphere model and the soft-sphere model. In this work is carried out a detailed study of contact models, focusing on soft-sphere model, based on a dynamic system modeled as nonlinear mass-spring-damper. In order to improve the nonlinear contact model, in this study it is proposed two new approximate relations for determining the damping coefficient and duration of contact for a specific nonlinear soft-sphere contact model where the contact force is continuous at the start and end of the contact. The methodology of the development of this work is divided into three parts: literature research of the contact models; analytical and numerical study of these models and test problems with numerical experiments, using the open source code MFIX (Multiphase Flow with Interphase eXchange). The proposed relations are analyzed and applied in three different problems: dynamic problem, gas-solid flow and granular flow. All results are compared with literature data showing good agreement for these cases studied in the present work.