Digital Commons Network^™

Analysis And Visualization Of Flow Fields Using Information-Theoretic Techniques And Graph-Based Representations, Jun Ma

Dissertations, Master's Theses and Master's Reports - Open

Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner.

My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow …

Access Control Programming Library And Exploration System, Zhitao Qiu

Dissertations, Master's Theses and Master's Reports - Open

The high complexity of advanced security models in the modern trusted systems requires an effective formal education for students. Education access control tools have been promoted. Though they can benefit the learning through analyzing or visualizing access control policies, few of them are designed to teach development of access control policies.

In this report, we propose an access control programming library which can provide students hand-on experience with the effect of an access control policy on a running program. A student can write a policy and then run programs under the policy. The Programming Library provides a system call wrapper …

Mower : A New Design For Non-Blocking Misprediction Recovery, Zhaoxiang Jin

Dissertations, Master's Theses and Master's Reports - Open

Mower is a micro-architecture technique which targets branch misprediction penalties in superscalar processors. It speeds-up the misprediction recovery process by dynamically evicting stale instructions and fixing the RAT (Register Alias Table) using explicit branch dependency tracking. Tracking branch dependencies is accomplished by using simple bit matrices. This low-overhead technique allows overlapping of the recovery process with instruction fetching, renaming and scheduling from the correct path. Our evaluation of the mechanism indicates that it yields performance very close to ideal recovery and provides up to 5% speed-up and 2% reduction in power consumption compared to a traditional recovery mechanism using a …

Generating Plans In Concurrent, Probabilistic, Over-Subscribed Domains, Li Li

Dissertations, Master's Theses and Master's Reports - Open

Planning in realistic domains typically involves reasoning under uncertainty, operating under time and resource constraints, and finding the optimal subset of goals to work on. Creating optimal plans that consider all of these features is a computationally complex, challenging problem. This dissertation develops an AO* search based planner named CPOAO* (Concurrent, Probabilistic, Over-subscription AO*) which incorporates durative actions, time and resource constraints, concurrent execution, over-subscribed goals, and probabilistic actions. To handle concurrent actions, action combinations rather than individual actions are taken as plan steps. Plan optimization is explored by adding two novel aspects to plans. First, parallel steps that serve …

Object-Based Classification Of Earthquake Damage From High-Resolution Optical Imagery Using Machine Learning, James Bialas

Dissertations, Master's Theses and Master's Reports - Open

Object-based approaches to the segmentation and supervised classification of remotely-sensed images yield more promising results compared to traditional pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods and trial and error are often used, but time consuming and yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time sensitive applications such as earthquake induced damage assessment.

Our research takes a systematic approach to evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely-sensed imagery using Trimble’s eCognition …