936 resultados para state dependent and time dependent rules
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Traditionally, densities of newly built roadways are checked by direct sampling (cores) or by nuclear density gauge measurements. For roadway engineers, density of asphalt pavement surfaces is essential to determine pavement quality. Unfortunately, field measurements of density by direct sampling or by nuclear measurement are slow processes. Therefore, I have explored the use of rapidly-deployed ground penetrating radar (GPR) as an alternative means of determining pavement quality. The dielectric constant of pavement surface may be a substructure parameter that correlates with pavement density, and can be used as a proxy when density of asphalt is not known from nuclear or destructive methods. The dielectric constant of the asphalt can be determined using ground penetrating radar (GPR). In order to use GPR for evaluation of road surface quality, the relationship between dielectric constants of asphalt and their densities must be established. Field measurements of GPR were taken at four highway sites in Houghton and Keweenaw Counties, Michigan, where density values were also obtained using nuclear methods in the field. Laboratory studies involved asphalt samples taken from the field sites and samples created in the laboratory. These were tested in various ways, including, density, thickness, and time domain reflectometry (TDR). In the field, GPR data was acquired using a 1000 MHz air-launched unit and a ground-coupled unit at 200 and 500 MHz. The equipment used was owned and operated by the Michigan Department of Transportation (MDOT) and available for this study for a total of four days during summer 2005 and spring 2006. The analysis of the reflected waveforms included “routine” processing for velocity using commercial software and direct evaluation of reflection coefficients to determine a dielectric constant. The dielectric constants computed from velocities do not agree well with those obtained from reflection coefficients. Perhaps due to the limited range of asphalt types studied, no correlation between density and dielectric constant was evident. Laboratory measurements were taken with samples removed from the field and samples created for this study. Samples from the field were studied using TDR, in order to obtain dielectric constant directly, and these correlated well with the estimates made from reflection coefficients. Samples created in the laboratory were measured using 1000 MHz air-launched GPR, and 400 MHz ground-coupled GPR, each under both wet and dry conditions. On the basis of these observations, I conclude that dielectric constant of asphalt can be reliably measured from waveform amplitude analysis of GJPR data, based on the consistent agreement with that obtained in the laboratory using TDR. Because of the uniformity of asphalts studied here, any correlation between dielectric constant and density is not yet apparent.
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Natural disasters in Argentina and Chile played a significant role in the state-formation and nation-building process (1822-1939). This dissertation explores state and society responses to earthquakes by studying public and private relief efforts reconstruction plans, crime and disorder, religious interpretations of catastrophes, national and transnational cultures of disaster, science and technology, and popular politics. Although Argentina and Chile share a political border and geological boundary, the two countries provide contrasting examples of state formation. Most disaster relief and reconstruction efforts emanated from the centralized Chilean state in Santiago. In Argentina, provincial officials made the majority of decisions in a catastrophe’s aftermath. Patriotic citizens raised money and collected clothing for survivors that helped to weave divergent regions together into a nation. The shared experience of earthquakes in all regions of Chile created a national disaster culture. Similarly, common disaster experiences, reciprocal relief efforts, and aid commissions linked Chileans with Western Argentine societies and generated a transnational disaster culture. Political leaders viewed reconstruction as opportunities to implement their visions for the nation on the urban landscape. These rebuilding projects threatened existing social hierarchies and often failed to come to fruition. Rebuilding brought new technologies from Europe to the Southern Cone. New building materials and systems, however, had to be adapted to the South American economic and natural environment. In a catastrophe’s aftermath, newspapers projected images of disorder and the authorities feared lawlessness and social unrest. Judicial and criminal records, however, show that crime often decreased after a disaster. Finally, nineteenth-century earthquakes heightened antagonism and conflict between the Catholic Church and the state. Conservative clergy asserted that disasters were divine punishments for the state’s anti-clerical measures and later railed against scientific explanations of earthquakes.
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The Technical College of the Lowcountry reports to the Budget and Control Board its annual accountability report that includes an executive summary, a description of the leadership system, customer focus and satisfaction and other performance criteria, mission, and program descriptions and budgets.
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The Technical College of the Lowcountry reports to the Budget and Control Board its annual accountability report that includes an executive summary, a description of the leadership system, customer focus and satisfaction and other performance criteria, mission, and program descriptions and budgets.
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The Technical College of the Lowcountry reports to the Budget and Control Board its annual accountability report that includes an executive summary, a description of the leadership system, customer focus and satisfaction and other performance criteria, mission, and program descriptions and budgets.
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The Technical College of the Lowcountry reports to the Budget and Control Board its annual accountability report that includes an executive summary, a description of the leadership system, customer focus and satisfaction and other performance criteria, mission, and program descriptions and budgets.
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Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.
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Slot and van Emde Boas Invariance Thesis states that a time (respectively, space) cost model is reasonable for a computational model C if there are mutual simulations between Turing machines and C such that the overhead is polynomial in time (respectively, linear in space). The rationale is that under the Invariance Thesis, complexity classes such as LOGSPACE, P, PSPACE, become robust, i.e. machine independent. In this dissertation, we want to find out if it possible to define a reasonable space cost model for the lambda-calculus, the paradigmatic model for functional programming languages. We start by considering an unusual evaluation mechanism for the lambda-calculus, based on Girard's Geometry of Interaction, that was conjectured to be the key ingredient to obtain a space reasonable cost model. By a fine complexity analysis of this schema, based on new variants of non-idempotent intersection types, we disprove this conjecture. Then, we change the target of our analysis. We consider a variant over Krivine's abstract machine, a standard evaluation mechanism for the call-by-name lambda-calculus, optimized for space complexity, and implemented without any pointer. A fine analysis of the execution of (a refined version of) the encoding of Turing machines into the lambda-calculus allows us to conclude that the space consumed by this machine is indeed a reasonable space cost model. In particular, for the first time we are able to measure also sub-linear space complexities. Moreover, we transfer this result to the call-by-value case. Finally, we provide also an intersection type system that characterizes compositionally this new reasonable space measure. This is done through a minimal, yet non trivial, modification of the original de Carvalho type system.
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This paper proposes to use a state-space technique to represent a frequency dependent line for simulating electromagnetic transients directly in time domain. The distributed nature of the line is represented by a multiple 1t section network made up of the lumped parameters and the frequency dependence of the per unit longitudinal parameters is matched by using a rational function. The rational function is represented by its equivalent circuit with passive elements. This passive circuit is then inserted in each 1t circuit of the cascade that represents the line. Because the system is very sparse, it is possible to use a sparsity technique to store only nonzero elements of this matrix for saving space and running time. The model was used to simulate the energization process of a 10 km length single-phase line. ©2008 IEEE.
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215 p.
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The real effects of an imperfectly credible disinflation depend critically on the extent of price rigidity. Therefore, the study of how policymakers’ credibility affects the outcome of an announced disinflation should not be dissociated from the analysis of the determinants of the frequency of price adjustments. In this paper we examine how the policymaker’s credibility affects the outcome of an announced disinflation in a model with endogenous time-dependent pricing rules. Both the initial degree of price ridigity, calculated optimally, and, more notably, the changes in contract length during disinflation play an important role in the explanation of the effects of imperfect credibility. We initially evalute the costs of disinflation in a setup where credibility is exogenous, and then allow agents to update beliefs about the “type” of monetary authority that they face. We show that, in both cases, the interaction between the endogeneity of time-dependent rules and imperfect credibility increases the output costs of disinflation.
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Some dynamical properties for a Lorentz gas were studied considering both static and time-dependent boundaries. For the static case, it was confirmed that the system has a chaotic component characterized with a positive Lyapunov exponent. For the time-dependent perturbation, the model was described using a four-dimensional nonlinear map. The behaviour of the average velocity is considered in two different situations: (i) non-dissipative and (ii) dissipative dynamics. Our results confirm that unlimited energy growth is observed for the non-dissipative case. However, and totally new for this model, when dissipation via inelastic collisions is introduced, the scenario changes and the unlimited energy growth is suppressed, thus leading to a phase transition from unlimited to limited energy growth. The behaviour of the average velocity is described using scaling arguments. (C) 2010 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)