Real-Time Strategy (RTS) is a sub-genre of strategy games which is running in real-time, typically in a war setting. The player uses workers to gather resources, which in turn are used for creating new buildings, training combat units, build upgrades and do research. The game is won when all buildings of the opponent(s) have been destroyed. The numerous tasks that need to be handled in real-time can be very demanding for a player. Computer players (bots) for RTS games face the same challenges, and also have to navigate units in highly dynamic game worlds and deal with other low-level tasks such as attacking enemy units within fire range. This thesis is a compilation grouped into three parts. The first part deals with navigation in dynamic game worlds which can be a complex and resource demanding task. Typically it is solved by using pathfinding algorithms. We investigate an alternative approach based on Artificial Potential Fields and show how an APF based navigation system can be used without any need of pathfinding algorithms. In RTS games players usually have a limited visibility of the game world, known as Fog of War. Bots on the other hand often have complete visibility to aid the AI in making better decisions. We show that a Multi-Agent PF based bot with limited visibility can match and even surpass bots with complete visibility in some RTS scenarios. We also show how the bot can be extended and used in a full RTS scenario with base building and unit construction. In the next section we propose a flexible and expandable RTS game architecture that can be modified at several levels of abstraction to test different techniques and ideas. The proposed architecture is implemented in the famous RTS game StarCraft, and we show how the high-level architecture goals of flexibility and expandability can be achieved. In the last section we present two studies related to gameplay experience in RTS games. In games players usually have to select a static difficulty level when playing against computer oppo- nents. In the first study we use a bot that during runtime can adapt the difficulty level depending on the skills of the opponent, and study how it affects the perceived enjoyment and variation in playing against the bot. To create bots that are interesting and challenging for human players a goal is often to create bots that play more human-like. In the second study we asked participants to watch replays of recorded RTS games between bots and human players. The participants were asked to guess and motivate if a player was controlled by a human or a bot. This information was then used to identify human-like and bot-like characteristics for RTS game players.

Intermolecular potential energy functions for CO2 have been developed from first principles for use in heterogeneous systems, including one with explicit polarization. The intermolecular potentials have been expressed in a transferable form and parameterized from nearly exact electronic structure calculations. Models with and without explicit many-body polarization effects, known to be important in simulation of interfacial processes, are constructed. The models have been validated on pressure-density isotherms of bulk CO2 and adsorption in three metal-organic framework (MOF) materials. The present models appear to offer advantages over high quality fluid/liquid state potentials in describing CO2 interactions in interfacial environments where sorbates adopt orientations not commonly explored in bulk fluids. Thus, the nonpolar CO2-PHAST and polarizable CO2-PHAST* potentials are recommended for materials/interfacial simulations.

Electric end-use efficiency is attracting more and more attentions, but it remains unclear what factors are driving state policy innovations to improve energy efficiency. Controversy also exists over the effectiveness of energy efficiency programs. Several critical problems are facing the policymakers: what factors drive the states taking distinct strategies in policy innovation? Have state policies being able to improve energy efficiency in the past? And, will state policies remain relevant to future efficiency improvements? This dissertation tries to answer these important questions and assumes that policy innovation is relevant to energy efficiency. It first explores the factors that influence the adoption of energy efficiency policies using Internal Determinants models. Results suggest that internal state factors affect policy innovation, including state socioeconomic factors, state fiscal capacity, ideology, and constituent pressure. Policy innovations are found to be correlated with each other. This dissertation also evaluates the impact of policy innovation on energy efficiency by decomposing electricity productivity into activity, structure, and efficiency effects. The findings suggest that financial incentives and building codes have significant impacts on state electricity productivity. Other regulations tend to have mixed effects. In addition, an estimation of the achievable potential of energy efficiency suggests that policies will cost-effectively drive significant electricity savings in the future. Overall, this dissertation offers an in-depth diagnosis of the relationship between policy innovation and energy efficiency. It provides a rigorous statistical analysis covering the most important energy efficiency policies. It represents the first attempt to evaluate policy impact by decomposing electricity productivity. However, the statistical models and energy models are subject to limitations and future research is needed to improve the models.

Not available / text

Not available / text

Factorial designs have been widely used in many scientific and industrial settings, where it is important to distinguish "active'' or real factorial effects from "inactive" or noise factorial effects used to estimate residual or "error" terms. We propose a new approach to screen for active factorial effects from such experiments that utilizes the potential outcomes framework and is based on sequential posterior predictive model checks. One advantage of the proposed method lies in its ability to broaden the standard definition of active effects and to link their definition to the population of interest. Another important aspect of this approach is its conceptual connection to Fisherian randomization tests. As in the literature in design of experiments, the unreplicated case receives special attention and extensive simulation studies demonstrate the superiority of the proposed Bayesian approach over existing methods. The unreplicated case is also thoroughly explored. Extensions to three level and fractional factorial designs are discussed and illustrated using a classical seat belt example for the former and part of a stem-cell research collaborative project for the latter. / Statistics

A new polymer with dibenzo[a,e]cyclooctatetraene as the actuation center and one of the thiophene derivatives, 3,4-ethylenedioxythiophene, as polymer chain is successfully synthesized. Nuclear magnetic resonance spectrum is obtained for each synthetic step. Several electrochemistry tests are done to examine the oxidation and reduction properties of the monomer and polymer. Cyclic voltammetry is used for the polymerization. Polymer is first grown on a metallic working electrode and further coated on an ITO plate. UV-Vis experiment is also done. A [pi] [arrow] [pi]* transition is observed as the primary polymer electronic absorption peak. Thickness of the polymer film is also recorded. / text

Source memory is defined as memory for not only the core aspect of some event, but additional contextual detail about that core aspect, or item. Source memory tasks are marked by their engagement of prefrontal cortex in addition to the brain circuits required by other episodic memory tasks. The dissertation examines the relationships among source memory accuracy, concurrent brain activity, and general cognitive principles derived from the study of episodic memory more generally. Electrical measures of brain activity (event-related potentials, ERPs) were recorded while manipulating factors hypothesized to improve or worsen source memory accuracy.The first experiment manipulated the task assigned during the encoding phase and its match to the retrieval demands of remembering objects (depicted in drawings) and their colors. As predicted by the principle of transfer-appropriate processing, source accuracy was higher when the encoding task fostered integration of the item (object) and source (color) attributes. Prefrontal activity during the retrieval phase was greatly reduced when retrieval could benefit from transfer-appropriate processing.In associative memory tasks, poor memory performance is observed when the to-be-retained stimuli share elements with other studied stimuli, as in a variety of interference paradigms. The second experiment thus examined the impact of feature overlap on source recognition by varying the quantitative mapping between the shape and color of an object depicted in a drawing. The results showed two frontal processes supporting source retrieval: an early differentiation between stimuli identical to those encoded and those that switch colors from study to test, and a later effect reflecting prolonged memory search that was truncated by reinstating unique object-color pairings at test.The final experiment compared conjunctions of "intra-item" versus "extra-item" features, by placing the features within a single visual object or distributing them across two visual objects. Source accuracy was worse when shape and color were spatially separated, but prefrontal activity did not vary. The insensitivity of prefrontal ERPs to this perceptual manipulation of difficulty stands in contrast to their sensitivity to encoding task. Individual variability in parietal ERPs was strongly correlated with source accuracy, and likely reflects a contribution of visual working memory to long-term memory.

The possibilities and implications of photons within the infrared, visible, and ultraviolet behaving as sources of intracellular and intercellular communication and information were investigated experimentally for melanoma cells during the 24 hrs following removal from incubation. Specific wavelengths during different intervals were associated with specific classes of biomolecules that were predicted based on the physical properties associated with their amino acid sequences. Application of a specific intensity and physiologically patterned magnetic field predicted from a model that applied the concept of magnetic moment to the whole cell resulted in photon emissions. They were detected at distances sufficient to allow intercellular communication. The occurrence of macroscopic entanglement or non-locality was shown between two loci of where simple chemically-based photons emissions were generated. Within all three experiments there was marked quantitative congruence between the energies associated with the power density of the photon emissions and the physicochemical variables involved with their reduction. These results indicate that photon emissions coupled with classic biomolecular pathways and processes may behave as intra- and inter-cellular sources of information that could control the complex dynamics of cells. The effect may not depend upon locality but exhibit non-local characteristics.

The self-potential method responds to the electrokinetic phenomenon of streaming potential and has been applied in hydrogeologic and engineering investigations to aid in the evaluation of subsurface hydraulic conditions. Of specific interest is the application of the method to embankment dam seepage monitoring and detection. This demands a quantitative interpretation of seepage conditions from the geophysical data. To enable the study of variably saturated flow problems of complicated geometry, a three-dimensional finite volume algorithm is developed to evaluate the self-potential distribution resulting from subsurface fluid flow. The algorithm explicitly calculates the distribution of streaming current sources and solves for the self-potential given a model of hydraulic head and prescribed distributions of the streaming current cross-coupling conductivity and electrical resistivity. A new laboratory apparatus is developed to measure the streaming potential coupling coefficient and resistivity in unconsolidated soil samples. Measuring both of these parameters on the same sample under the same conditions enables us to properly characterize the streaming current cross-coupling conductivity coefficient. I present the results of a laboratory investigation to study the influence of soil and fluid parameters on the cross-coupling coefficient, and characterize this property for representative well-graded embankment soils. The streaming potential signals associated with preferential seepage through the core of a synthetic embankment dam model are studied using the forward modelling algorithm and measured electrical properties to assess the sensitivity of the self-potential method in detecting internal erosion. Maximum self-potential anomalies are shown to be linked to large localized hydraulic gradients that develop in response to piping, prior to any detectable increase in seepage flow through the dam. A linear inversion algorithm is developed to evaluate the three-dimensional distribution of hydraulic head from self-potential data, given a known distribution of the cross-coupling coefficient and electrical resistivity. The inverse problem is solved by minimizing an objective function, which consists of a data misfit that accounts for measurement error and a model objective function that incorporates a priori information. The algorithm is suitable for saturated flow problems or where the position of the phreatic surface is known.