This dissertation is a technological study that deals with those techniques employed by the Gault Clovis people in the manufacture of both bifaces and blades. The materials studied were recovered during the 2000 and 2001 field seasons conducted by the Anthropology Department of Texas A&M University. The study involves an analysis that deals with raw material selection, blank production, reduction methods, and problems encountered, and includes a definitive description and metric calculations for each of the various artifact types analyzed. The results are then compared to similar artifact assemblages from known Clovis sites. The conclusions derived from this analysis show that the Gault Clovis people utilized a number of different strategies in both biface and blade reduction. It was found that some of these strategies, previously felt to be restricted to one reductive procedure, were connected and utilized in both procedures. In addition, it was discovered that some techniques thought to be limited to use only within the initial reduction sequence were, in fact, utilized throughout.

Made available in DSpace on 2015-03-26T13:32:15Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1216352 bytes, checksum: 3e5fbc09a6f684ddf7dbb4442657ce1f (MD5) Previous issue date: 2012-07-26 / The main contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. Under this approach, genome-wide selection (GWS) can be used with this purpose. GWS consists in analyzing of a large number of SNP markers widely distributed in the genome, and due to the fact that the number of markers is much larger than the number of genotyped individuals (high dimensionality) and also to the fact that such markers are highly correlated (multicollinearity). However, the use of methodologies that address the adversities is fundamental to the success of genome wide selection. In view of, the aim of this dissertation was to propose the application of Independent Component Regression (ICR), Principal Component Regression (PCR), Partial Least Squares (PLS) and Random Regression Best Linear Unbiased Predictor, whereas carcass traits in an F2 population of pigs originated from the cross of two males from the naturalized Brazilian breed Piau with 18 females of a commercial line (Large White × Landrace × Pietrain), developed at the University Federal of Viçosa. The specific objectives were, to estimate Genomic Breeding Value (GBV) for each individual and estimate the effects of SNP markers in order to compare methods. The results showed that ICR method is more efficient, since provided most accurate genomic breeding values estimates for most carcass traits. / A principal contribuição da genética molecular no melhoramento animal é a utilização direta das informações de DNA no processo de identificação de animais geneticamente superiores. Sob esse enfoque, a seleção genômica ampla (Genome Wide Selection GWS), a qual consiste na análise de um grande número de marcadores SNPs (Single Nucleotide Polymorphisms) amplamente distribuídos no genoma, foi idealizada. A utilização dessas informações é um desafio, uma vez que o número de marcadores é muito maior que o número de animais genotipados (alta dimensionalidade) e tais marcadores são altamente correlacionados (multicolinearidade). No entanto, o sucesso da seleção genômica ampla deve-se a escolha de metodologias que contemplem essas adversidades. Diante do exposto, o presente trabalho teve por objetivo propor a aplicação dos métodos de regressão via Componentes Independentes (Independent Component Regression ICR), regressão via componentes principais (Principal Component Regression PCR), regressão via Quadrados Mínimos Parciais (Partial Least Squares PLSR) e RR-BLUP, considerando características de carcaça em uma população F2 de suínos proveniente do cruzamento de dois varrões da raça naturalizada brasileira Piau com 18 fêmeas de linhagem comercial (Landrace × Large White × Pietrain), desenvolvida na Universidade Federal de Viçosa. Os objetivos específicos foram estimar Valores Genéticos Genômicos (Genomic Breeding Values GBV) para cada indivíduo avaliado e estimar efeitos de marcadores SNPs, visando a comparação dos métodos. Os resultados indicaram que o método ICR se mostrou mais eficiente, uma vez que este proporcionou maiores valores de acurácia na estimação do GBV para a maioria das características de carcaça.

In large data, set of mined association rules are typically large in number and hard to interpret. Some grouping and pruning methods have been developed to make rules more understandable. In this study, one of these methods is modified to be more effective and more efficient in applications including low thresholds for support or confidence, such as association analysis of product/process quality improvement. Results of experiments on benchmark datasets show that the proposed method groups and prunes more rules. In the literature, many rule reduction methods, including grouping and pruning methods, have been proposed for different applications. The variety in methods makes it hard to select the right method for applications such those of quality improvement. In this study a novel performance comparison basis is introduced to address this problem. It is applied here to compare the improved method to the original one. The introduced basis is tailored for quality data, but is flexible and can be changed to be applicable in other application domains.

In this study, theorem-based, generally applicable stochastic parameterisation schemes are developed and applied to a quasi-geostrophic model of extratropical atmospheric low-frequency variability (LFV). Hasselmann’s method is developed from limiting theorems for slow-fast systems of ordinary differential equations (ODEs) and applied to this high-dimensional model of intermediate complexity comprised of partial differential equations (PDEs) with complicated boundary conditions. Seamless, efficient algorithms for integrating the parameterised models are developed, which require only minimal changes to the full model algorithm. These algorithms may be readily adapted to a range of climate models of greater complexity in parameterising the effects of fast, sub-grid scale processes on the resolved scales. For comparison, the Majda-Timofeyev-Vanden-Eijnden (MTV) parameterisation method is applied to this model. The seamless algorithms are first adapted to probe the multiple regime behaviour that characterises the full model LFV. In contrast to the conclusions of a previous study, it is found that the multiple regime behaviour is not the result of a nonlinear interaction between the leading two planetary-scale modes, but rather is the result of interactions among these two modes and the leading synoptic-scale mode. The low-dimensional Hasselmann stochastic models perform well in simulating the statistics of the planetary-scale modes. In particular, a model with only one resolved (planetary-scale) mode captures the multiple regime behaviour of the full model. Although a fast-evolving synoptic-scale mode is of primary importance to the multiple regime behaviour, deterministic averaged forcing and not multiplicative noise is responsible for the regime behaviour in this model. The MTV models generate non-Gaussian statistics, but generally do not perform as well in capturing the climate statistics.

Submitted by JÚLIO HEBER SILVA (julioheber@yahoo.com.br) on 2016-12-08T17:49:42Z No. of bitstreams: 2 Dissertação - Daniel Ferreira Gonçalves - 2016.pdf: 6039771 bytes, checksum: 9dd76bacc79e08f02f565c3a309abedd (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2016-12-13T18:06:03Z (GMT) No. of bitstreams: 2 Dissertação - Daniel Ferreira Gonçalves - 2016.pdf: 6039771 bytes, checksum: 9dd76bacc79e08f02f565c3a309abedd (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-12-13T18:06:03Z (GMT). No. of bitstreams: 2 Dissertação - Daniel Ferreira Gonçalves - 2016.pdf: 6039771 bytes, checksum: 9dd76bacc79e08f02f565c3a309abedd (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-03-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Studies focused on modeling and mechanical system behavior prediction are relevant to the avoidance of excessive deflections and structural failures. Most of these systems are discretized by finite element models which are constituted by a large number of degrees of freedom, making it quite expensive computationally. In this context, the application of models reduction methods becomes particularly prominent because it provides a greater saving in time, keeping the solution quality. This work aims to study methods of reducing models applied to nonlinear dynamical systems. Among the methods aimed at reducing models, there is the Guyan method, Improved Reduction System (IRS), Iterative Improved Reduction System (IIRS) System Equivalent Reduction Expansion Process (SEREP), Component Mode Synthesis (CMS) and method of modal projection. In order to verify the efficiency of the models reduction methods when applied to nonlinear systems is presented in this paper a study where the system responses are analyzed by checking the computational cost and quality of the reduced solution of the problem for each of the mentioned methods. / Estudos voltados à modelagem e previsão do comportamento de sistemas mecânicos são relevantes na coibição de deflexões excessivas e falhas estruturais. A maioria destes sistemas são discretizados por elementos finitos cujos modelos são constituídos por elevado número de graus de liberdade tornando-se bastante oneroso computacionalmente. Neste contexto, a aplicação de métodos de redução de modelos ganha destaque especial pois proporciona maior economia de tempo, mantendo a qualidade de solução. Este trabalho tem por objetivo o estudo de métodos de redução de modelos aplicados a sistemas dinâmicos não lineares. Dentre os métodos voltados à redução de modelos, destaca-se o método de Guyan, Improved Reduction System (IRS), Iterative Improved Reduction System (IIRS), System Equivalent Reduction Expansion Process (SEREP), Component Mode Synthesis (CMS) e método da Base Modal. Com o objetivo de verificar a eficiência dos métodos de redução de modelos quando aplicados em sistemas não lineares, é apresentado neste trabalho um estudo onde são analisadas as respostas do sistema, verificando o custo computacional e a qualidade da solução do problema reduzido para cada um dos métodos citados.

<div><div>In this thesis, we focus on two challenges arising in kinetic equations, high dimensions and uncertainties. To reduce the dimensions, we proposed efficient methods for linear Boltzmann and full Boltzmann equations based on dynamic low-rank frameworks. For linear Boltzmann equation, we proposed a method that is based on macro-micro decomposition of the equation; the low-rank approximation is only used for the micro part of the solution. The time and spatial discretizations are done properly so that the overall scheme is second-order accurate (in both the fully kinetic and the limit regime) and asymptotic-preserving (AP). That is, in the diffusive regime, the scheme becomes a macroscopic solver for the limiting diffusion equation that automatically captures the low-rank structure of the solution. Moreover, the method can be implemented in a fully explicit way and is thus significantly more efficient compared to the previous state of the art. We demonstrate the accuracy and efficiency of the proposed low-rank method by a number of four-dimensional (two dimensions in physical space and two dimensions in velocity space) simulations. We further study the adaptivity of low-rank methods in full Boltzmann equation. We proposed a highly efficient adaptive low- rank method in Boltzmann equation for computations of steady state solutions. The main novelties of this approach are: On one hand, to the best of our knowledge, the dynamic low- rank integrator hasn’t been applied to full Boltzmann equation till date. The full collision operator is local in spatial variable while the convection part is local in velocity variable. This separated nature is well-suited for low-rank methods. Compared with full grid method (finite difference, finite volume,...), the dynamic low-rank method can avoid the full computations of collision operators in each spatial grid/elements. Resultingly, it can achieve much better efficiency especially for some low rank flows (e.g. normal shock wave). On the other hand, our adaptive low-rank method uses a novel dynamic thresholding strategy to adaptively control the computational rank to achieve better efficiency especially for steady state solutions. We demonstrate the accuracy and efficiency of the proposed adaptive low rank method by a number of 1D/2D Maxwell molecule benchmark tests. On the other hand, for kinetic equations with uncertainties, we focus on non-intrusive sampling methods where we are able to inherit good properties (AP, positivity preserving) from existing deterministic solvers. We propose a control variate multilevel Monte Carlo method for the kinetic BGK model of the Boltzmann equation subject to random inputs. The method combines a multilevel Monte Carlo technique with the computation of the optimal control variate multipliers derived from local or global variance minimization prob- lems. Consistency and convergence analysis for the method equipped with a second-order positivity-preserving and asymptotic-preserving scheme in space and time is also performed. Various numerical examples confirm that the optimized multilevel Monte Carlo method outperforms the classical multilevel Monte Carlo method especially for problems with dis- continuities<br></div></div>

The high mass X-ray binary 4U 2206+54 has been a very controversial system due to variability in spectral data as well as photometric data. We, at Brigham Young University, have been observing this system in multiple filters with several telescopes. This thesis presents our methods of observations, reductions, and results. It also compares what we have been detecting to other groups looking at the same target in different wavelengths. Furthermore, this thesis discusses some of the peculiarities of 4U 2206+54 and possible theories to explain these phenomena. Based on our photometric observations for the past three years, we believe the period of 4U 2206+54 is 25.1 days. Furthermore, spectral data show an unusual double-peaked Hα feature. We believe the primary star BD +53°2790 is a single star, and that the system is surrounded by a gas and dust shell.

Em diferentes aplicações de Aprendizado de Máquina podemos estar interessados na minimização do valor esperado de certa função de perda. Para a resolução desse problema, Otimização estocástica e Sample Size Selection têm um papel importante. No presente trabalho se apresentam as análises teóricas de alguns algoritmos destas duas áreas, incluindo algumas variações que consideram redução da variância. Nos exemplos práticos pode-se observar a vantagem do método Stochastic Gradient Descent em relação ao tempo de processamento e memória, mas, considerando precisão da solução obtida juntamente com o custo de minimização, as metodologias de redução da variância obtêm as melhores soluções. Os algoritmos Dynamic Sample Size Gradient e Line Search with variable sample size selection apesar de obter soluções melhores que as de Stochastic Gradient Descent, a desvantagem se encontra no alto custo computacional deles. / In different Machine Learnings applications we can be interest in the minimization of the expected value of some loss function. For the resolution of this problem, Stochastic optimization and Sample size selection has an important role. In the present work, it is shown the theoretical analysis of some algorithms of these two areas, including some variations that considers variance reduction. In the practical examples we can observe the advantage of Stochastic Gradient Descent in relation to the processing time and memory, but considering accuracy of the solution obtained and the cost of minimization, the methodologies of variance reduction has the best solutions. In the algorithms Dynamic Sample Size Gradient and Line Search with variable sample size selection, despite of obtaining better solutions than Stochastic Gradient Descent, the disadvantage lies in their high computational cost.

Nowadays, increasing pressure from legislation and customer demands in the automotive industry are forcing manufacturers to produce greener vehicles with lower emissions and fuel consumption.As a result, electrified and hybrid vehicles are a growing popular alternative to traditional internal combustion engines (ICE). The noise from an electric vehicle comes mainly from contact between tyres and road, wind resistance and driveline. The noise emitted from the driveline is for the mostpart related to the gearbox. When developing a driveline, it is a factor of importance to estimate the noise radiating from the gearbox to achieve an acceptable design.Gears are used extensively in the driveline of electric vehicles. As the gears are in mesh, a main intrusive concern is known as gear whine noise. Gear whine noise is an undesired vibroacoustic phenomenon and is likely to originate through the gear contacts and be transferred through themechanical components to the housing where the vibrations are converted into airborne and structure-borne noise. The gear whine noise originates primarily from the excitation coming from transmission error (TE). Transmission error is defined as the difference between the ideal smoothtransfer of motion of a gear and what is in practice due to lack of smoothness.The main objective of this study is to simulate the vibrations generated by the gear whine noise in an electric powertrain line developed by AVL Vicura. The electric transmission used in this study provides only a fixed overall gear ratio, i.e. 9.59, under all operation conditions. It is assumed thatthe system is excited only by the transmission error and the mesh stiffness of the gear contacts. In order to perform NVH analysis under different operating conditions, a multibody dynamics model according to the AVL Excite program has been developed. The dynamic simulations are thencompared with previous experimental measurements provided by AVL Vicura.Two validation criteria have been used to analyse the dynamic behaviour of the AVL Excite model: signal processing using the FFT method and comparison with the experimental measurements.The results from the AVL Excite model show that the FFT criterion is quite successful and all excitation frequencies are properly observed in FFT plots. Nevertheless, when it comes to the second criterion, as long as not all dynamic parameters of the system such as damping or stiffnesscoefficients are provided with certainty in the model, it is too difficult to investigate the accuracy of the AVL Excite model. Another investigation is a numerical design study to analyses how the damping coefficients influence the response. After reducing the damping parameters, the results show that the housing and bearings have the highest influence on the response. If more acceptable results are desired,future studies must be concentrated on these to obtain more acceptable damping values. / För närvarande tvingar ökat tryck från lagstiftning och kundkrav inom bilindustrin tillverkarna attproducera grönare fordon med lägre utsläpp och bränsleförbrukning. Som ett resultat ärelektrifierade och hybridfordon ett växande populärt alternativ till traditionellaförbränningsmotorer (ICE). Bullret från ett elfordon kommer främst från kontakten mellan däckoch väg, vindmotstånd och drivlinan. Bullret från drivlinan är i huvudsak relaterat till växellådan.Vid utveckling av en drivlina är det av betydelse att uppskatta bullret från växellådan för att uppnåen acceptabel design.Utväxlingar används i stor utsträckning i elfordons drivlina. Eftersom kugghjulen är i kontaktuppstår ett huvudproblem som är känt som ett vinande ljud från kugghjulskontakten.Kugghjulsljud är ett oönskat vibro-akustiskt fenomen och uppstår sannolikt på grund avkugghjulkontakterna och överförs via de mekaniska komponenterna till växellådshuset därvibrationerna omvandlas till luftburet och strukturburet ljud. Kugghjulsljudet härstammarhuvudsakligen från exciteringen som kommer från transmissionsfel (TE) i kugghjulskontakten.Överföringsfelet definieras som skillnaden mellan den ideala smidiga rörelseöverföringen hoskugghjulen och rörelsen som sker i verkligheten på grund av ojämnheter.Huvudsyftet med denna studie är att simulera vibrationerna som genereras avkugghjulskontakterna i en elektrisk drivlina utvecklad av AVL Vicura. Den elektriska drivlinan somanvänds i denna studie har endast ett fast utväxlingsförhållande, dvs 9,59, för alladriftsförhållanden. Det antas att systemet är exciterat endast av överföringsfelet och kugghjulensstyvhet i kuggkontakterna. För att kunna utföra NVH-analys under olika driftsförhållanden har enstelkroppsdynamikmodell utvecklats med hjälp av programmet AVL Excite. De dynamiskasimuleringarna jämförs sedan med tidigare experimentella mätningar som tillhandahålls av AVLVicura.Två valideringskriterier har använts för att analysera det dynamiska beteendet hos AVL Excitemodellen:signalbehandling med FFT-metoden och jämförelse med experimentella mätningar.Resultaten från AVL Excite-modellen visar att FFT-kriteriet är ganska framgångsrikt och allaexcitationsfrekvenser observeras korrekt i FFT-diagrammen. Men när det gäller det andra kriteriet,så länge som inte alla dynamiska parametrar i systemet, såsom dämpnings- ellerstyvhetskoefficienter, är tillförlitliga i modellen, är det för svårt att undersöka exaktheten hos AVLExcite-modellen.En annan undersökning som utförts är en numerisk designstudie för att analysera hurdämpningskoefficienterna påverkar responsen. Efter minskning av dämpningsparametrarna visarresultaten att växellådshus och lager har störst inflytande på resultatet. Om mer acceptabla resultatär önskvärda måste framtida studier koncentreras på dessa parametrar för att uppnå mer acceptabladämpningsvärden.

Em diferentes aplicações de Aprendizado de Máquina podemos estar interessados na minimização do valor esperado de certa função de perda. Para a resolução desse problema, Otimização estocástica e Sample Size Selection têm um papel importante. No presente trabalho se apresentam as análises teóricas de alguns algoritmos destas duas áreas, incluindo algumas variações que consideram redução da variância. Nos exemplos práticos pode-se observar a vantagem do método Stochastic Gradient Descent em relação ao tempo de processamento e memória, mas, considerando precisão da solução obtida juntamente com o custo de minimização, as metodologias de redução da variância obtêm as melhores soluções. Os algoritmos Dynamic Sample Size Gradient e Line Search with variable sample size selection apesar de obter soluções melhores que as de Stochastic Gradient Descent, a desvantagem se encontra no alto custo computacional deles. / In different Machine Learnings applications we can be interest in the minimization of the expected value of some loss function. For the resolution of this problem, Stochastic optimization and Sample size selection has an important role. In the present work, it is shown the theoretical analysis of some algorithms of these two areas, including some variations that considers variance reduction. In the practical examples we can observe the advantage of Stochastic Gradient Descent in relation to the processing time and memory, but considering accuracy of the solution obtained and the cost of minimization, the methodologies of variance reduction has the best solutions. In the algorithms Dynamic Sample Size Gradient and Line Search with variable sample size selection, despite of obtaining better solutions than Stochastic Gradient Descent, the disadvantage lies in their high computational cost.