Types computer science dissertations

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Queryable Expert Systems a. Although they have been shown to be useful, people find them difficult to query in flexible ways. This limits the reusability of the knowledge they contain.

Databases and noninteractive rule systems such as logic programs, on the other hand, are queryable but they do not offer an interview capability. This thesis is the first investigation that we know of into query-processing for interactive expert systems. In our query paradigm, the user describes a hypothetical condition and then the system reports which of its conclusions are reachable, and which are inevitable, under that condition. Gaussian mixture models are population density representations formed by the weighted linear combination of multiple, multivariate Gaussian component distributions.

Computer Science Thesis / Dissertation

Finite Gaussian mixture models are formed when a finite number of discrete component distributions are used. CGMMs are formed when multiple continua of component distributions are used. GGoF functions quantify how well a Gaussian having a particular mean and covariance represents the local distribution of samples. In this dissertation, Monte Carlo simulations are used to evaluate the robustness of a variety of GGoF functions and binning methods for the specifications of GGoF cores. In generalized projective Gaussian distributions, similar feature vectors, when projected onto a subset of basis feature vectors, have a Gaussian distribution.

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Additionally, CGMMs do not suffer from the problems associated with determining an appropriate number of components, initializing the component parameters, or iteratively converging to a solution. Generalized projective Gaussian distributions exist in a variety of real-world data. The applicability of CGMM via GGoF cores to real-world data is demonstrated through the accurate modeling of tissues in an inhomogeneous magnetic resonance image.

The extension of CGMM via GGoF cores to high-dimensional data is demonstrated through the accurate modeling of a sampled trivariate anisotropic generalized projective Gaussian distribution. However, many Augmented Reality applications will not be accepted unless virtual objects are accurately registered with their real counterparts. Good registration is difficult, because of the high resolution of the human visual system and its sensitivity to small differences.

Dynamic errors are usually the largest errors. This dissertation demonstrates that predicting future head locations is an effective approach for significantly reducing dynamic errors. This demonstration is performed in real time with an operational Augmented Reality system. First, evaluating the effect of prediction requires robust static registration. Therefore, this system uses a custom optoelectronic head-tracking system and three calibration procedures developed to measure the viewing parameters.

Second, the system predicts future head positions and orientations with the aid of inertial sensors. Effective use of these sensors requires accurate estimation of the varying prediction intervals, optimization techniques for determining parameters, and a system built to support real-time processes. On average, prediction with inertial sensors is 2 to 3 times more accurate than prediction without inertial sensors and 5 to 10 times more accurate than not doing any prediction at all. Prediction is most effective at short prediction intervals, empirically determined to be about 80 milliseconds or less.

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An analysis of the predictor in the frequency domain shows the predictor magnifies the signal by roughly the square of the angular frequency and the prediction interval. For specified head-motion sequences and prediction intervals, this analytical framework can also estimate the maximum possible time-domain error and the maximum tolerable system delay given a specified maximum time-domain error.

Future steps that may further improve registration are discussed. Data flow analysis is a technique for collecting information about the flow of data within computer programs. It is used by optimizing compilers in order to insure the correctness of optimizations as well as by certain program debugging aids. This dissertation introduces an iterative technique, called the method of attributes, for performing global data flow analysis using a parse tree representation of the source program.

It is applied to analysis of live variables and to analysis of available expressions; in both cases, time required for analysis of GOTO- less programs is linear in program size with a small constant of linearity , regardless of the nesting depth of program loops.

The method of attributes is applied to demand analysis of live variables. Computing Reviews Categories 4. This dissertation explores the problem of inserting virtual computer generated objects into natural scenes in video-based augmented-reality AR systems. The augmented-reality system problems addressed are the shorter-term goal of making synthetic objects appear to be more stable and registered and the longer-term goal of presenting proper occlusion and interaction cues between real and synthetic objects. These results can be achieved in video-based AR systems by directly processing video images of the natural scene in real-time.

No additional hardware or additional tracking mechanisms are needed above those currently used in augmented-reality systems. This means that either cheaper tracking systems could be used or possibly even no separate tracking system in certain situations. This is the first step toward further work of properly shading and lighting synthetic objects inserted into natural scenes. A real-time 30 Hz AR system is demonstrated which uses simple image feature tracking to improve registration and tracking accuracy.


This is extended to a more general system which illustrates how reconstruction of natural scene geometry, correct synthetic and real object occlusion, and collision detection could be achieved in real-time. A camera calibration appendix contains accuracy measurements.

Distinguished Dissertations in Computer Science

High-speed, high-quality computer graphics enables a user to interactively manipulate surfaces in four dimensions and see them on a computer screen. Surfaces in 4-space exhibit properties that are prohibited in 3-space. For example, nonorientable surfaces may be free of self-intersections in 4-space. Can a user actually make sense of the shapes of surfaces in a larger-dimensional space than the familiar 3D world? Experiment shows he can. A prototype system called Fourphront, running on the graphics engine Pixel-Planes 5 developed at UNC-Chapel Hill allows the user to perform interactive algorithms in order to determine some of the properties of a surface in 4-space.

This dissertation describes solutions to several problems associated with manipulating surfaces in 4-space. It shows how the user in 3-space can control a surface in 4-space in an intuitive way. It describes how to extend the common illumination models to large numbers of dimensions. And it presents visualization techniques for conveying 4D depth information, for calculating intersections, and for calculating silhouettes.

Significant user effort is required to choose recipients of shared information, which grows as the scale of the number of potential or target recipients increases. It is our thesis that it is possible to develop new approaches to predict persistent named groups, ephemeral groups, and response times that will reduce user effort. We predict persistent named groups using the insight that implicit social graphs inferred from messages can be composed with existing prediction techniques designed for explicit social graphs, thereby demonstrating similar grouping patterns in email and communities.

However, this approach still requires that users know when to generate such predictions. We predict group creation times based on the intuition that bursts of change in the social graph likely signal named group creation. While these recommendations can help create new groups, they do not update existing ones. We predict how existing named groups should evolve based on the insight that the growth rates of named groups and the underlying social graph will match. When appropriate named groups do not exist, it is useful to predict ephemeral groups of information recipients.

We have developed an approach to make hierarchical recipient recommendations that groups the elements in a flat list of recommended recipients, and thus is composable with existing flat recipient-recommendation techniques. It is based on the insight that groups of recipients in past messages can be organized in a tree. To help users select among alternative sets of recipients, we have made predictions about the scale of response time of shared information, based on the insights that messages addressed to similar recipients or containing similar titles will yield similar response times.

Our prediction approaches have been applied to three specific systems — email, Usenet and Stack Overflow — based on the insight that email recipients correspond to Stack Overflow tags and Usenet newsgroups. We evaluated these approaches with actual user data using new metrics for measuring the differences in scale between predicted and actual response times and measuring the costs of eliminating spurious named-group predictions, editing named-group recommendations for use in future messages, scanning and selecting hierarchical ephemeral group-recommendations, and manually entering recipients.

The light transport equation, conventionally known as the rendering equation in a slightly different form, is an implicit integral equation, which represents the interactions of light with matter and the distribution of light in a scene. This research describes a signals-and-systems approach to light transport and casts the light transport equation in terms of convolution.

Additionally, the light transport problem is linearly decomposed into simpler problems with simpler solutions, which are then recombined to approximate the full solution. The central goal is to provide interactive photorealistic rendering of virtual environments. We show how the light transport problem can be cast in terms of signals-and-systems. The light is the signal and the materials are the systems.

Even though the theoretical approach is presented in directional-space, we present an approximation in screen-space, which enables the exploitation of graphics hardware convolution for approximating the light transport equation.

The convolution approach to light transport is not enough to fully solve the light transport problem at interactive rates with current machines. We decompose the light transport problem into simpler problems. The decomposition of the light transport problem is based on distinct characteristics of different parts of the problem: the ideally diffuse, the ideally specular, and the glossy transfers.

A technique for interactive rendering of each of these components is presented as well as a technique for superposing the independent components in a multipass manner in real time. For about fifteen years, computer scientists have known how to prove that programs meet mathematical specifications. Among these are the difficulty of rigorously defining the function of a program, and the fact that the proofs of correctness tend to be much longer and much more complex that the programs themselves. We have tackled this problem from two sides.

First, we deal with proving compilers correct, a special class of programs for which there exists a rather simple specification of purpose. Second, although we would prefer to have programs which are guaranteed to be correct, we will accept a program where we can easily determine if the output of any given run is correct. People will generally be satisfied with a program that usually runs properly, but will always produce a message if it has not.