Autonomous agents may not have access to complete information about the state of the environment. For example, a robot soccer player may only be able to estimate the locations of other players not in the scope of its sensors. However, even though all the information needed for ideal decision making cannot be sensed, all that is sensed is usually not needed. The noise and motion of spectators, for example, can be ignored in order to focus on the game field. Standard formulations do not consider this situation, assuming that all the can be sensed must be included in any useful abstraction. This dissertation extends the Markov Decision Process Homomorphism framework (Ravindran, 2004) to partially observable domains, focusing specically on reducing Partially Observable Markov Decision Processes (POMDPs) when the model is known. This involves ignoring aspects of the observation function which are irrelevant to a particular task. Abstraction is particularly important in partially observable domains, as it enables the formation of a smaller domain model and thus more efficient use of the observed features.

Conventional analysis of atmospheric data includes three-dimensional desktop-computer displays. One disadvantage is that it can reduce the ability to zoom in and see small-scale features while concurrently viewing other faraway features. This research intends to determine if using virtual environments to examine atmospheric data can improve a meteorologist's ability to analyze the given information. In addition to possibly enhancing small-scale analysis, virtual environments technology offers an array of possible improvements. Presented is the theory on developing an experiment to establish the extent to which virtual environments assist meteorologists in analysis. Following is the details of an implementation of such an experiment. Based on the quantitative results obtained, the conclusion is that immersion can significantly increase the accuracy of a meteorologist's analysis of an atmospheric data set.

No description available.

No description available.

No description available.

No description available.

The development of novel bioremediation systems has widespread benefits for human health and natural ecosystems. Optimization of such systems is only possible with a thorough understanding of the processes that drive bioremediation. This thesis developed novel understanding of carbon sources and cycling relationships for microbial communities that are integral in controlling contaminant fate in two contaminated environments. In the first case (Chapter 2), biodegradation in the soil microbial community was determined to be the primary pathway for recalcitrant petroleum pollutant removal. Microbial uptake and metabolism of petroleum hydrocarbons was conclusively demonstrated via 14C analysis of their PLFA biomarkers. This microbial community was the most 14C depleted bacterial system detected in an environmental system to date. In addition, complete mineralization of petroleum carbon was demonstrated with 14C analysis of soil COz. The second paper (Chapter 3) identified unique Phospholipid Fatty Acid (PLFA) biomarkers and stable carbon isotopic fractionation patterns for heterotrophic and autotrophic bacterial communities of an acid mine drainage (AMD) system. The characteristic isotopic fractionations observed during biosynthesis of PLF A biomarkers in autotrophic versus heterotrophic metabolic pathways provided the basis for a model capable of elucidating the relative roles of these members of the microbial community in the environment. The major implications of the knowledge developed in this thesis, are two new methods to identify microbial carbon cycling pathways and processes in contaminated environments. These advances may lead to new methods for mitigating the effects of contamination in environmental systems through better understanding of the microbial processes at the contaminated sites. / Thesis / Master of Science (MSc)

Speech enhancement in multi-speaker babble remains an enormous challenge. In this study, we developed a binaural speech enhancement system to extract information pertaining to a target speech signal embedded in a noisy background for use in future hearing-aid systems. The principle underlying the proposed system is to simulate the perceptual auditory segregation process carried out in the normal human auditory system. Based on the spatial location, pitch and onset cues, the system can identify and enhance those time-frequency regions which constitute the target speech. The proposed system is capable of dealing with a wide variety of noise intrusions, including competing speech signals and multi-speaker babble. It also works under mild reverberation conditions. Systematic evaluation shows that the system achieves substantial improvement on the intelligibility of target signal, while it largely suppresses the unwanted background signal. / Thesis / Master of Applied Science (MASc)

Across domains, researchers, engineers, and designers are faced with large volumes of data that are heterogeneous in nature - including spatial, abstract, and temporal information. There are numerous design and technical challenges when considering the unification, management, and presentation of these information types. Most research and applications have focused on display techniques for each of the information types individually, but much less in known about how to represent the relationships between information types. This research explores the perceptual and usability impacts of data representations and layout algorithms for the next-generation of integrated information spaces. We propose Information-Rich Virtual Environments (IRVEs) as a solution to challenges of integrated information spaces. In this presentation, we will demonstrate the application requirements and foundational technology of IRVEs and articulate crucial tradeoffs in IRVE information design. We will present a design space and evaluation methodology to explore the usability effects of these tradeoffs. Experimental results will be presented for a series of empirical usability evaluations that increase our understanding of how these tradeoffs can be resolved to improve user performance. Finally, we interpret the results though the models of Information Theory and Human Information Processing to derive new conclusions regarding the role of perceptual cues in determining user performance in IRVEs. These lessons are posed as a set of design guidelines to aid developers of new IRVE interfaces and specifications. / Ph. D.

The undergraduate Computer Science program at Virginia Tech is the largest in the Commonwealth of Virginia, of which a key component is ``CS 1044: Introduction to Programming'', and is typical of a first course in computer programming throughout the USA. While the student access to learning resources has improved considerably with the development of web-based assets, students are still expected to use the same sophisticated program development tools as are used in industry. The perceived complexity of the learning environment currently in use drives many women and minority students from the Computer Science program. A great deal of attention has been paid to the need to administer the student assignments and the grading system for this course, so as to minimize the teaching/grading load, but little attention has been paid to the methodologies of learning the material through practice. The work reported herein is intended to improve the pedagogy of this course by creating and integrating teaching/learning tools that better manage the student's engagement in the use of program development activities. Following the implementation of a three-element software system involving an interpreter for the C-language, a program development environment, and a data-monitoring/collectiondevice, the system was deployed in support of the freshman course in parallel to the commercial system commonly used. The experiment concentrated on examining the impact of the simplified development environment and the effort required for students to complete assigned programming projects. / Ph. D.