Although understanding causation is an essential part of nearly every problem domain, it has resisted formal treatment in the languages of logic, probability, and even statistics. Autonomous artificially intelligent agents need to be able to reason about cause and effect. One approach is to provide the agent with formal, computational notions of causality that enable the agent to deduce cause and effect relationships from observations. During the 1990s, formal notions of causality were pursued within the AI community by many researchers, notably by Judea Pearl. Pearl developed the formal language of structural models for reasoning about causation. Among the problems he addressed in this formalism was a problem common to both AI and law, the attribution of causal responsibility or actual causation. Pearl and then Halpern and Pearl developed formal definitions of actual causation in the language of structural models. <p>Within the law, the traditional test for attributing causal responsibility is the counterfactual "but-for" test, which asks whether, but for the defendant's wrongful act, the injury complained of would have occurred. This definition conforms to common intuitions regarding causation in most cases, but gives non-intuitive results in more complex situations where two or more potential causes are present. To handle such situations, Richard Wright defined the NESS Test. Pearl claims that the structural language is an appropriate language to capture the intuitions that motivate the NESS test. While Pearl's structural language is adequate to formalize the NESS test, a recent result of Hopkins and Pearl shows that the Halpern and Pearl definition fails to do so, and this thesis develops an alternative structural definition to formalize the NESS test.

Computers play an increasingly large part in childrens daily lives, yet most interface design research has focused on adult users. One area of research that has informed adult interface design is the Media Equation, which explains how people respond to media in a fundamentally social manner and how they treat computers as social actors in interactions. To date, it was unknown whether these findings apply to children as well. This thesis investigates the effects of the Media Equation on children in three specific areas: praise, team formation, and politeness. It also examines whether varying the form of the computer affects the Media Equation in any way and whether there are any gender differences in how children respond to the Media Equation. <p> Little evidence was found to support the existence of Media Equation effects on children. Children responded positively regardless of whether any Media Equation elements were incorporated into the interfaces. These results raise doubts on whether there is any added value to including Media Equation principles into the design of childrens interfaces. The results do, however, shed some light on children-computer interaction and lead to a set of guidelines for designers of childrens technology.

The cubic focusing nonlinear Schrodinger equation is a canonical model equation that arises in physics and engineering, particularly in nonlinear optics and plasma physics. Cubic NLS is an accessible venue to refine techniques for more general nonlinear partial differential equations. In this thesis, it is shown there exist solutions to the focusing cubic nonlinear Schrodinger equation in three dimensions that blowup on a circle, in the sense of L2-norm concentration on a ring, bounded H1-norm outside any surrounding toroid, and growth of the global H1-norm with the log-log rate. Analogous behaviour occurs in higher dimensions. That is, there exists data for which the corresponding evolution by the cubic nonlinear Schrodinger equation explodes on a set of co-dimension two. To simplify the exposition, the proof is presented in dimension three, with remarks to indicate the adaptations in higher dimension.

The cubic focusing nonlinear Schrodinger equation is a canonical model equation that arises in physics and engineering, particularly in nonlinear optics and plasma physics. Cubic NLS is an accessible venue to refine techniques for more general nonlinear partial differential equations. In this thesis, it is shown there exist solutions to the focusing cubic nonlinear Schrodinger equation in three dimensions that blowup on a circle, in the sense of L2-norm concentration on a ring, bounded H1-norm outside any surrounding toroid, and growth of the global H1-norm with the log-log rate. Analogous behaviour occurs in higher dimensions. That is, there exists data for which the corresponding evolution by the cubic nonlinear Schrodinger equation explodes on a set of co-dimension two. To simplify the exposition, the proof is presented in dimension three, with remarks to indicate the adaptations in higher dimension.

En esta tesis se analiza de manera detallada los sistemas de refrigeración solar con equipos de absorción de doble efecto con captadores solares de concentración en términos de energía primaria consumida. El análisis de estos sistemas permite compararlos con sistemas de refrigeración por absorción de simple efecto accionados con energía solar térmica de baja temperatura y con sistemas convencionales de compresión. Estos tres tipos de sistemas han sido modelizados mediante el software de simulación TRNSYS para cubrir la demanda frigorífica de un edificio genérico de oficinas localizado en Sevilla (España). Un aspecto importante en esta tesis es la modelización de las enfriadoras de absorción de simple y doble efecto mediante el método de la ecuación característica. Este método permite modelizar las prestaciones térmicas del equipo de absorción de manera sencilla y robusta, además que debido a su estructura puede ser aplicado a cualquier sistema de refrigeración por absorción. / This thesis presents a detailed analysis of solar cooling systems, with double-effect absorption chillers activated by concentrating solar collectors, in terms of primary energy savings. This analysis allows comparing this type of systems with solar assisted air-conditioning installations composed by single-effect absorption chillers and flat plate solar collectors, and conventional compression systems. These three types of systems have been modeled in a TRNSYS simulation environment and applied to a generic building located in the city of Seville (Spain) to cover its cooling demand. An important aspect of this thesis is the modeling of single and double-effect absorption chillers by means of the characteristic equation method (ChEM). This method permits modeling of thermal performance of the absorption machine in a simple and robust manner, and due to its structure, the method can be applied to any absorption refrigeration system.

There are two sources of information available in empirical research in finance: one corresponding to historical data and the other to prices currently observed in the markets. When proposing a model, it is desirable to use information from both sources. However in modern finance, where stochastic differential equations have been one of the main modeling tools, the common models are typically different for historical data and for current market data. The former are usually assumed to be time homogeneous, while the latter are typically time in-homogeneous. This practice can be explained by the fact that a time-homogeneous model is stationary and easier to estimate, while time-inhomogeneous model are required in order to replicate market data sufficiently well without creating arbitrage opportunities. In this thesis, we study methods of statistical inference, both parametric and non-parametric, for stochastic differential equations with time-dependent parameters. In the first part, we propose a new class of stochastic differential equation with time-dependent drift and diffusion terms, where some of the parameters change according to a hidden Markov process. We show that under some technical conditions this innovative way of modeling switching times renders the resulting model stationary. We also explore different approaches to estimate parameters in our proposed model. Our simulation studies demonstrate that the parameters of the model can be efficiently estimated by using a version of the filtering method proposed in the literature. We illustrate our model and the proposed estimation method by applying them to interest rate data, and we detect significant time variations in early 1980s, when targets of the monetary policy in the United States were changed. One of the known drawbacks of parametric models is the risk of model misspecification. In the second part of the thesis, we allow the drift to be time-dependent and nonparametric, and our objective is to estimate it using a single trajectory of the process. The main idea underlying this method is to approximate the time-dependent function with a sequence of polynomials. Since we can estimate efficiently only a finite number of parameters for any finite length of data, in our method we propose to relate the number of parameters to the length of the observed trajectory. This idea is similar to the method of sieves proposed by Grenander (Abstract Inference, 1981). The asymptotic analysis that we present is based on the assumption that the length of available data $T$ increases to infinity. We investigate two cases, one is a Brownian motion with time-dependent drift and the other corresponds to a class of mean-reverting stochastic differential equations with time-dependent mean-reversion level. In both cases we prove asymptotic consistency and normality of a modified maximum likelihood estimator of the projected time-dependent component. The main challenge in proving our results in the second case stems from two features of the problem: one is due to the fact that coefficients of projections change with $T$ and the other is related to the confounding effect between the mean-reversion speed and the level function. By applying our method to the same interest rate data we use in the first part, we find another evidence of time-variation in the drift term.

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Seagrass bed is a highly productivity ecosystem, it also provides habitats for animals and plays an important role in stabilizing the substrate. The sea anemone Phymanthus strandesi is very abundant in the seagrass bed of Thalassia hemprichii on Hsiao-Liuchiu Island. Structural Equation Modeling (SEM) was used to investigate the relationship between P. strandesi and some environmental factors, which affect the distribution of this species at Tuozaiping tidal flat (N 22¢X20"55' E 120¢X21"49'), Hsiao-Liuchiu Island. Light and temperature were also manipulated in the laboratory to test their effect on the hiding response of P. strandesi. The results of SEM show that the abundance of T. hemprichii showed very weak positive relation with P.strandesi. On the other hand, soil depth on the seagrass bed might be the main factor that affects the distribution of P. strandesi. In high a temperature situation (i.e. over 38¢XC), all the sea anemones in the experimental container hided into the sand. However, only some sea anemones hid when exposed to strong light (i.e. 5030 lum/ft²) after one and half hours.

In this thesis, we develop and test a fundamentally new linear-discontinuous least-squares (LDLS) method for spatial discretization of the one-dimensional (1-D) discrete-ordinates (SN) equations. This new scheme is based upon a least-squares method with a discontinuous trial space. We implement our new method, as well as the lineardiscontinuous Galerkin (LDG) method and the lumped linear-discontinuous Galerkin (LLDG) method. The implementation is in FORTRAN. We run a series of numerical tests to study the robustness, L2 accuracy, and the thick diffusion limit performance of the new LDLS method. By robustness we mean the resistance to negativities and rapid damping of oscillations. Computational results indicate that the LDLS method yields a uniform second-order error. It is more robust than the LDG method and more accurate than the LLDG method. However, it fails to preserve the thick diffusion limit. Consequently, it is viable for neutronics but not for radiative transfer since radiative transfer problems can be highly diffusive.

We present a new iterative approach to solving neutral-particle transport problems. The scheme divides the transport solution into its particular and homogeneous or “source-free” components. The particular problem is solved directly, while the homogeneous problem is found iteratively. To organize the iterative inversion of the homogeneous components, we exploit the structures of the so called Case-modes that compose it. The asymptotic Case-modes, those that vary slowly in space and angle, are assigned to a diffusion solver. The remaining transient Case-modes, those with large spatial gradients, are assigned to a transport solver. The scheme iterates on the contribution from each solver until the particular plus homogeneous solution converges. The iterative method is implemented successfully in slab geometry with isotropic scattering and one energy group. The convergence rate of the method is only weakly dependent on the scattering ratio of the problem. Instead, the rate of convergence depends strongly on the material thickness of the slab, with thick slabs converging in few iterations. The transient solution is obtained by applying a One Cell Inversion scheme instead of a Source Iteration based scheme. Thus, the transient unknowns are calculated with little coordination between them. This independence among unknowns makes our scheme ideally suited for transport calculations on parallel architectures. The slab geometry iterative scheme is adapted to XY geometry. Unfortunately, this attempt to extend the slab geometry iterative scheme to multiple dimensions has not been successful. The exact filtering scheme needed to discriminate asymptotic and transient modes has not been obtained and attempts to approximate this filtering process resulted in a divergent iterative scheme. However, the development of this iterative scheme yield valuable analysis tools to understand the Case-mode structure of any spatial discretization under arbitrary material properties.