This thesis describes a model of speech timing, predicting at the syllable level, with sensitivity to rhythmic factors at the foot level, that predicts segmental durations by a process of accommodation into the higher-level timing framework. The model is based on analyses of two large databases of British English speech; one illustrating the range of prosodic variation in the language, the other illustrating segmental duration characteristics in various phonetic environments. Designed for a speech synthesis application, the model also has relevance to linguistic and phonetic theory, and shows that phonological specification of prosodic variation is independent of the phonetic realisation of segmental duration. It also shows, using normalisation of phone-specific timing characteristics, that lengthening of segments within the syllable is of three kinds: prominence-related, applying more to onset segments; boundary-related, applying more to coda segments; and rhythm/rate-related, being more uniform across all component segments. In this model, durations are first predicted at the level of the syllable from consideration of the number of component segments, the nature of the rhyme, and the three types of lengthening. The segmental durations are then constrained to sum to this value by determining an appropriate uniform quantile of their individual distributions. Segmental distributions define the range of likely durations each might show under a given set of conditions; their parameters are predicted from broad-class features of place and manner of articulation, factored for position in the syllable, clustering, stress, and finality. Two parameters determine the segmental duration . pdfs, assuming a Gamma distribution, and one parameter determines the quantile within that pdf to predict the duration of any segment in a given prosodic context. In experimental tests, each level produced durations that closely fitted the data of four speakers of British English, and showed performance rates higher than a comparable model predicting exclusively at the level of the segment.

Este trabalho apresenta um modelo de otimização multiobjetivo aplicado ao projeto de concepção de submarinos convencionais (i.e. de propulsão dieselelétrica). Um modelo de síntese que permite a estimativa de pesos, volume, velocidade, carga elétrica e outras características de interesse para a o projeto de concepção é formulado. O modelo de síntese é integrado a um modelo de otimização multiobjetivo baseado em algoritmos genéticos (especificamente, o algoritmo NSGA II). A otimização multiobjetivo consiste na maximização da efetividade militar do submarino e na minimização de seu custo. A efetividade militar do submarino é representada por uma Medida Geral de Efetividade (OMOE) estabelecida por meio do Processo Analítico Hierárquico (AHP). O Custo Básico de Construção (BCC) do submarino é estimado a partir dos seus grupos de peso. Ao fim do processo de otimização, é estabelecida uma Fronteira de Pareto composta por soluções não dominadas. Uma dessas soluções é selecionada para refinamento preliminar e os resultados são discutidos. Subsidiariamente, esta dissertação apresenta discussão sucinta sobre aspectos históricos e operativos relacionados a submarinos, bem como sobre sua metodologia de projeto. Alguns conceitos de Arquitetura Naval, aplicada ao projeto dessas embarcações, são também abordados. / This thesis presents a multi-objective optimization model applied to concept design of conventional submarines (i.e. diesel-electric powered boats). A synthesis model that allows the estimation of weights, volume, speed, electrical load and other design features of interest is formulated. The synthesis model is integrated with a multi-objective optimization model based on genetic algorithms (specifically, the NSGA II algorithm). The multi-objective optimization consists of maximizing the submarine\'s military effectiveness and minimizing its cost. The military effectiveness is represented by an Overall Measure of Effectiveness (OMOE) established via the Analytic Hierarchy Process (AHP). The submarine\'s Basic Construction Cost (BCC) is estimated from its weight groups. At the end of the optimization process, a Pareto Front composed of non-dominated solutions is established. One of these solutions is selected for preliminary refinement and the results are discussed. This work also presents succinct discussion about submarine historical and operational aspects and design methodology. Some Naval Architectural concepts, applied to submarine design, are also discussed.

Population synthesis models (PSMs) are fundamental tools to study the star formation history and IMF of unresolved stellar populations using spectral features. This work presents a new set of PSMs constructed using theoretical isochrones and two state-ofthe- art synthetic spectral libraries. The BT-Settl and Munari libraries were chosen for their ability to predict the observed values of Lick-type and IMF-sensitive indices in individual stars of the solar neighbourhood. The BT-Settl library was used to sample the cool main sequence stars and the Munari library for the rest of the evolutionary phases. The PSMs cover a range of metallicities with [Fe/H]= 0, -1.31 and -1.81 for scaled-solar and α-enhanced metal mixtures. The models were used to study the behaviour of the IMF indices defined in the literature and the results are in good agreement with what other PSMs have determined. The PSMs in this work predict a strong degeneracy between age, metallicity and IMF. I used the models to study which are the main evolutionary phases contributing to each IMF-sensitive index and found that most indices reach their final integrated values before the turn off. The post-main sequence stars contribute mainly to the continuum of these bands. Uncertainties in the the effective temperature of the isochrones can affect IMF estimates. The PSMs were applied to extragalactic globular clusters (GCs) and early-type galaxies (ETGs) using data from the literature. I determined the ages, metallicities and IMFs of these systems using index combinations in the optical and infrared. I explored how the morphology of the Horizontal Branch (HB) and dynamical evolution (which are key uncertainties in the modelling of GCs) can affect the IMF predictions. In a population with a Milky Way IMF, dynamical evolution can make the IMF indices mimic a bottom-light IMF. HB morphology has no impact on the IMF estimates at low [Fe/H]. In the IMF index-index diagrams for GCs, the results are significantly affected by the unknown sodium abundances of these systems. Using the PSMs in this work the best index combination to determine the IMF is CaH1 and TiO2. The ETGs and the [Fe/H]=0 GCs appear to have a bottom-heavy IMF with x ~ 3:0. These results are discussed in the work.

Este trabalho apresenta um modelo de otimização multiobjetivo aplicado ao projeto de concepção de submarinos convencionais (i.e. de propulsão dieselelétrica). Um modelo de síntese que permite a estimativa de pesos, volume, velocidade, carga elétrica e outras características de interesse para a o projeto de concepção é formulado. O modelo de síntese é integrado a um modelo de otimização multiobjetivo baseado em algoritmos genéticos (especificamente, o algoritmo NSGA II). A otimização multiobjetivo consiste na maximização da efetividade militar do submarino e na minimização de seu custo. A efetividade militar do submarino é representada por uma Medida Geral de Efetividade (OMOE) estabelecida por meio do Processo Analítico Hierárquico (AHP). O Custo Básico de Construção (BCC) do submarino é estimado a partir dos seus grupos de peso. Ao fim do processo de otimização, é estabelecida uma Fronteira de Pareto composta por soluções não dominadas. Uma dessas soluções é selecionada para refinamento preliminar e os resultados são discutidos. Subsidiariamente, esta dissertação apresenta discussão sucinta sobre aspectos históricos e operativos relacionados a submarinos, bem como sobre sua metodologia de projeto. Alguns conceitos de Arquitetura Naval, aplicada ao projeto dessas embarcações, são também abordados. / This thesis presents a multi-objective optimization model applied to concept design of conventional submarines (i.e. diesel-electric powered boats). A synthesis model that allows the estimation of weights, volume, speed, electrical load and other design features of interest is formulated. The synthesis model is integrated with a multi-objective optimization model based on genetic algorithms (specifically, the NSGA II algorithm). The multi-objective optimization consists of maximizing the submarine\'s military effectiveness and minimizing its cost. The military effectiveness is represented by an Overall Measure of Effectiveness (OMOE) established via the Analytic Hierarchy Process (AHP). The submarine\'s Basic Construction Cost (BCC) is estimated from its weight groups. At the end of the optimization process, a Pareto Front composed of non-dominated solutions is established. One of these solutions is selected for preliminary refinement and the results are discussed. This work also presents succinct discussion about submarine historical and operational aspects and design methodology. Some Naval Architectural concepts, applied to submarine design, are also discussed.

Computer hardware keeps increasing in complexity. Software design needs to keep up with this. The right models and abstractions empower developers to leverage the novelties of modern hardware. This thesis deals primarily with Models of Computation, as a basis for software design, in a family of methods called software synthesis. We focus on Kahn Process Networks and dataflow applications as abstractions, both for programming and for deriving an efficient execution on heterogeneous multicores. The latter we accomplish by exploring the design space of possible mappings of computation and data to hardware resources. Mapping algorithms are not at the center of this thesis, however. Instead, we examine the mathematical structure of the mapping space, leveraging its inherent symmetries or geometric properties to improve mapping methods in general. This thesis thoroughly explores the process of model-based design, aiming to go beyond the more established software synthesis on dataflow applications. We starting with the problem of assessing these methods through benchmarking, and go on to formally examine the general goals of benchmarks. In this context, we also consider the role modern machine learning methods play in benchmarking. We explore different established semantics, stretching the limits of Kahn Process Networks. We also discuss novel models, like Reactors, which are designed to be a deterministic, adaptive model with time as a first-class citizen. By investigating abstractions and transformations in the Ohua language for implicit dataflow programming, we also focus on programmability. The focus of the thesis is in the models and methods, but we evaluate them in diverse use-cases, generally centered around Cyber-Physical Systems. These include the 5G telecommunication standard, automotive and signal processing domains. We even go beyond embedded systems and discuss use-cases in GPU programming and microservice-based architectures.