No description available.

Every moment of every day, at least hundreds of thousands of tires roll across a surface throughout the world. Tires are indisputably important in our daily life. The tire's primary component is rubber, which consumes energy when it rotates on a substrate due to the viscoelastic material's internal friction: a phenomenon referred to as rolling resistance. The interaction between the tire and the road surface is one of the most intricate and crucial phenomena in an automobile, because it is responsible for creating forces, moments, and deformation in the tire. Additionally, the road's roughness interacts with the tire and contributes significantly to its performance. This dissertation aims to develop a comprehensive physics-based model for predicting the rolling resistance of a viscoelastic material due to dynamic deformations caused by tire rotation using an analytical approach. The model was developed by proposing a Gaussian wave function propagating across a tire circumference's viscoelastic medium. The wave function was selected to describe the displacement field produced by tire-road interaction. Additionally, by adopting a multi-scale modeling technique, the model was upgraded to estimate rolling resistance while taking into account surface roughness at all length scales, from macroscopic to microscopic. Additionally, another mathematical model was developed using the Fourier series approach to evaluate the steady-state stress response and energy dissipation for any harmonic and non-harmonic periodic strain signals. Additionally, the dissertation strove to build a continuum damage mathematical model using a combined testing/modeling methodology to predict the aging of Styrene-Butadiene Rubber (SBR) after continuous exposure to the atmosphere. The obtained model was developed through the implementation of optimization techniques while formulating a mathematical model, which was then combined with a physics-based model to predict rolling resistance while taking into account rubber aging. Calibration of hyperelastic and viscoelastic material models with testing data was performed using an optimization technique that yielded sufficient results. The results of all mathematical models obtained in this dissertation are reported subsequently. The stress response of a viscoelastic material under harmonic and non-harmonic strain input yielded good agreement with the FEA model obtained using ABAQUS. The rolling resistance behavior under various operating conditions, including texture and aging effects, was reported, and the results aligned with the experimental results found in the literature. / Doctor of Philosophy / Every moment of every day, hundreds of thousands of automobile tires roll across a surface somewhere in the world. A tire is an undeniably important part of everyday life. Rubber is the tire's main component, and when it rotates on a surface, it loses energy, resulting in a force that resists motion, known as rolling resistance force. The contact between the tire and the road is one of the most complicated and important phenomena that happens in an automobile because it is responsible for the vehicle's dynamic performance in areas such as acceleration, stopping distance, and stability. Another factor that affects tire and car performance and should be taken into account is the road's roughness. This dissertation used an analytical method to come up with an accurate physics-based model for predicting the rolling resistance force of a viscoelastic material caused by tire rotation. The model was developed by assuming a Gaussian wave function would move across the tire circumference. Additionally, using a multi-scale modeling technique, the model was improved so that it could calculate the value of rolling resistance force considering surface roughness in all lengths of scale. This project also developed an additional mathematical model using the Fourier series method to determine how the stress response and energy dissipation would behave for any harmonic and nonharmonic periodic strain signals. Additionally, the dissertation presents the developing of a continuum damage mathematical model that could predict the material property of styrene-butadiene rubber (SBR) after being exposed to the air for a long time (i.e., aged). The model was developed based on experimental data and optimization techniques. This model was then combined with a physics-based model to predict rolling resistance force while taking aging into account. The material models were defined using an optimization method that yielded good results. The stress response of a viscoelastic material when it was subjected to harmonic and non-harmonic strain was in good agreement with the Finite Element Analysis (FEA) model made with ABAQUS. Rolling resistance behavior was observed, and the results were consistent with those found in the literature.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Lie-detection has been an evergreen and evolving subject. Polygraph techniques have been the most popular and successful technique till date. The main drawback of the polygraph is that good results cannot be attained without maintaining a physical contact, of the subject under test. In general, this physical contact would induce extra consciousness in the subject. Also, any sort of arousal in the subject triggers false positives while performing the traditional polygraph based tests. With all these drawbacks in the polygraph, also, due to rapid developments in the fields of computer vision and artificial intelligence, with newer and faster algorithms, have compelled mankind to search and adapt to contemporary methods in lie-detection. Observing the facial expressions of emotions in a person without any physical contact and implementing these techniques using artificial intelligence is one such method. The concept of magnifying a micro expression and trying to decipher them is rather premature at this stage but would evolve in future. Magnification using EVM technique has been proposed recently and it is rather new to extract these micro expressions from magnified EVM based on HOG features. Till date, HOG features have been used in conjunction with SVM, and generally for person/pedestrian detection. A newer, simpler and contemporary method of applying EVM with HOG features and Back-propagation Neural Network jointly has been introduced and proposed to extract and decipher the micro-expressions on the face. Micro-expressions go unnoticed due to its involuntary nature, but EVM is used to magnify them and makes them noticeable. Emotions behind the micro-expressions are extracted and recognized using the HOG features \& Back-Propagation Neural Network. One of the important aspects that has to be dealt with human beings is a biased mind. Since, an investigator is also a human and, he too, has to deal with his own assumptions and emotions, a Neural Network is used to give the investigator an unbiased start in identifying the true emotions behind every micro-expression. On the whole, this proposed system is not a lie-detector, but helps in detecting the emotions of the subject under test. By further investigation, a lie can be detected. / This thesis uses a magnification technique to magnify the subtle, faint and spontaneous facial muscle movements or more precisely, micro-expressions. This magnification would help a system in classifying them and estimating the emotion behind them. This technique additionally magnifies the color changes, which could be used to extract the pulse without a physical contact with the subject. The results are presented in a GUI. / Gautam: +46(0)739528573, +91-9701534064 Tushal: +46(0)723219833, +91-9000242241 Venu: +46(0)734780266, +91-9298653191 Sai: +91-9989410111

Cryo-electron microscopy (cryo-EM) has been established as the leading imaging technique for structural studies from small proteins to whole cells at a molecular level. The great advances in cryo-EM have led to the ability to provide unique insights into a wide variety of biological processes in a close to native, hydrated state at near-atomic resolutions. The developments of computational approaches have significantly contributed to the exciting achievements of cryo-EM. This dissertation emphasizes new approaches to address image processing problems in cryo-EM, including tilt series alignment evaluation, simultaneous determination of sample thickness, tilt, and electron mean free path based on Beer-Lambert law, Model-Based Iterative Reconstruction (MBIR) on tomographic data, minimization of objective lens astigmatism in instrument alignment and defocus and magnification dependent astigmatism of TEM images. The final goal of these methodological developments is to improve the 3D reconstruction of cryo-EM and visualize more detailed characterization.

This dissertation is a collection of essays on challenges in international trade and international finance, which apply econometric methods to diverse data sets and relate them to economic policy questions. In times of crises, the question, whether individual countries have the ability to pursue idiosyncratic monetary policy, is important. The degree of integration and comovement between financial markets, for instance, is critical to better assess the real threat facing a country in a crisis. Also, from a macroeconomic modeling perspective, there has recently been a renewed interest in the cyclical and long-run comovement of interest rates. Hence, in a first essay, we reinvestigate the long- and short-run comovements in the G7-countries by conducting tests for cointegration, common serial correlation and codependence with nominal and real interest rates. Overall, we only find little evidence of comovements: common trends are occasionally observed, but the majority of interest rates are not cointegrated. Although some evidence for codependence of higher order can be found in the pre-Euro area sample, common cycles appear to exist only in rare cases. We argue that some earlier, more positive findings in the literature are difficult to reconcile due to differing assumptions about the underlying stochastic properties of interest rates. Hence, we conclude that they cannot be generalized for all interest rates, time periods, and reasonable alternative estimation procedures. This finding indicates that scope for individual countries to pursue stabilization policy does still exist in a globalized world. Emerging economies, in general, are much more exposed and vulnerable to crises than industrialized countries. Accordingly, stabilization policy is especially important in these countries and the selection of the best monetary regime is essential. This is why, in a second essay, we contrast two different views in the debate on official dollarization: the Mundell (1961) framework of optimum currency areas and a model on boom-bust cycles by Schneider and Tornell (2004), who take account of credit market imperfections prevalent in middle income countries. We highlight the strikingly different role of the exchange rate in the two models. While in the Mundell framework the exchange rate is expected to smooth the business cycle, the second model predicts the exchange rate to play an amplifying role. We empirically evaluate both models for eight highly dollarized Central American economies. We document the existence of credit market imperfections and find that shocks from the exchange rate indeed amplify business cycles in these countries. Using a new method proposed by Cubadda (1999 and 2007), we furthermore test for cyclical comovement and reject the hypothesis that the selected countries form an optimum currency area with the United States according to the Mundell definition. In the context of the recent global crisis, globalization and vertical integration in particular were often blamed for being the cause for the severe trade crisis. For that reason, in the essay that contributes to the trade literature, we analyze the role of international supply chains in explaining the long-run trade elasticity and its short-term volatility in the context of the recent trade collapse. We adopt an empirical strategy based on two steps: first, stylized facts on long- and short-term trade elasticity are derived from exploratory analysis and formal modeling on a large and diversified sample of countries. Then, we derive observations of interrelated input-output matrices for a demonstrative sub-set of countries. We find evidence for two supply chain related factors to explain the overshooting of trade elasticity during the 2008-2009 trade collapse: the composition and the bullwhip effect. However, evidence for a magnification effect could not be found. Overall, we do not accept the hypothesis that international supply chains explain all by themselves the changes in trade-income elasticity.