We discuss the problem of embedding planar graphs onto the plane with pre-specified vertex locations. In particular, we introduce a method for constructing such an embedding for both the case where the mapping from the vertices onto the vertex locations is fixed and the case where this mapping can be chosen. Moreover, the technique we present is sufficiently abstract to generalize to a method for constructing simultaneous planar embeddings with fixed vertex locations. In all cases, we are concerned with minimizing the number of bends per edge in the embeddings we produce. In the case where the mapping is fixed, our technique guarantees embeddings with at most 8n - 7 bends per edge in the worst case and, on average, at most 16/3n - 1 bends per edge. This result improves previously known techniques by a significant constant factor. When the mapping is not pre-specified, our technique guarantees embeddings with at most O(n^(1 - 2^(1-k))) bends per edge in the worst case and, on average, at most O(n^(1 - 1/k)) bends per edge, where k is the number of graphs in the simultaneous embedding. This improves upon the previously known O(n) bound on the number of bends per edge for k at least 2. Moreover, we give an average-case lower bound on the number of bends that has similar asymptotic behaviour to our upper bound.

Successfully inducing malolactic fermentation in the production of grape wines can be challenging, especially in wines after finishing alcoholic fermentation with limited energy sources, low pH values and high ethanol concentrations. In this thesis, the kinetics of several chemicals of enological relevance were studied in a white wine (Chardonnay) and a red wine (Cab Franc) vinified by traditional, consecutive alcoholic (AF) and malolactic fermentations (MLF), and simultaneous AF/MLF, where bacteria were co-inoculated with yeast. The Chardonnay must was adjusted to four pH values (3.20, 3.35, 3.50 or 3.65), the cab Franc was kept as original pH value (3.56) and the concentrations of sugars, organic acids as well as acetaldehyde were followed throughout the fermentations. For Chardonnay the degradation of glucose and fructose was slower at the lowest must pH value (3.20) and independent from the time of bacterial inoculation. In all cases, malolactic conversion was faster after yeast-bacterial co-inoculation and was completed in simultaneous treatments at pH values of 3.35-3.65, and consecutive treatments at pH 3.50 and 3.65. No statistically significant difference was observed among the final acetic acid concentration, in all inoculation and pH treatments. For Cab Franc, it confirmed that co-inoculation shortened the fermentation periods while having minor effects on other parameters. Overall, simultaneous AF/MLF allowed for greatly reduced fermentation times, while the must pH remained a strong factor for fermentation success and determined the final concentration of various wine components. The time of inoculation influenced formation and degradation kinetics of organic acids and acetaldehyde significantly.

The use of a simultaneous prompting procedure for teaching choice-making skills using an iPad to high-school students with moderate intellectual disabilities was evaluated. The Proloquo2Go application, which is designed for use with the iPad, iPod touch, or iPhone as an augmentative alternative communication system for individuals with communication support needs, was used to communicate choices made by participants during sessions. A multiple-probe design across 3 participants was used to evaluate the effectiveness of the simultaneous prompting instructional procedure to teach independent choice making. Results indicate the procedure was effective for teaching all participants to use an iPad to make choices from foods and drinks available for lunch, and 2 participants generalized choice-making skills to a novel set of stimuli.

Reliable and accurate positioning systems are expected to significantly improve the safety for first responders and enhance their operational efficiency. To be effective, a first responder positioning systemmust provide room level accuracy during extended time periods of indoor operation. This thesis presents a system which combines a zero-velocity-update (ZUPT) aided inertial navigation system (INS), using a foot-mounted inertial measurement unit (IMU), with the use of opportunistic multi-frequency received signal strength (RSS) measurements. The system does not rely on maps or pre-collected data from surveys of the radio-frequency (RF environment; instead, it builds its own database of collected rss measurements during the course of the operation. New RSS measurements are continuously compared with the stored values in the database, and when the user returns to a previously visited area this can thus be detected. This enables loop-closures to be detected online, which can be used for error drift correction. The system utilises a distributed particle simultaneous localisation and mapping (DP-SLAM) algorithm which provides a flexible 2-D navigation platform that can be extended with more sensors. The experimental results presented in this thesis indicates that the developed rss slam algorithm can, in many cases, significantly improve the positioning performance of a foot-mounted INS.

Doctor of Philosophy (PhD) / This thesis addresses the problem of building statistical models for multi-sensor perception in unstructured outdoor environments. The perception problem is divided into three distinct tasks: recognition, representation and association. Recognition is cast as a statistical classification problem where inputs are images or a combination of images and ranging information. Given the complexity and variability of natural environments, this thesis investigates the use of Bayesian statistics and supervised dimensionality reduction to incorporate prior information and fuse sensory data. A compact probabilistic representation of natural objects is essential for many problems in field robotics. This thesis presents techniques for combining non-linear dimensionality reduction with parametric learning through Expectation Maximisation to build general representations of natural features. Once created these models need to be rapidly processed to account for incoming information. To this end, techniques for efficient probabilistic inference are proposed. The robustness of localisation and mapping algorithms is directly related to reliable data association. Conventional algorithms employ only geometric information which can become inconsistent for large trajectories. A new data association algorithm incorporating visual and geometric information is proposed to improve the reliability of this task. The method uses a compact probabilistic representation of objects to fuse visual and geometric information for the association decision. The main contributions of this thesis are: 1) a stochastic representation of objects through non-linear dimensionality reduction; 2) a landmark recognition system using a visual and ranging sensors; 3) a data association algorithm combining appearance and position properties; 4) a real-time algorithm for detection and segmentation of natural objects from few training images and 5) a real-time place recognition system combining dimensionality reduction and Bayesian learning. The theoretical contributions of this thesis are demonstrated with a series of experiments in unstructured environments. In particular, the combination of recognition, representation and association algorithms is applied to the Simultaneous Localisation and Mapping problem (SLAM) to close large loops in outdoor trajectories, proving the benefits of the proposed methodology.

Zugl.: Berlin, Techn. Universiẗat, Diss., 2007.

Thesis (M.E.E.)--University of Delaware, 2007. / Principal faculty advisor: Guang R. Gao, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Zugl.: Erlangen, Nürnberg, Univ., Diss., 2005

Thesis (Ph. D.)--State University of New York at Binghamton, Department of Computer Science, 2006. / Includes bibliographical references (leaves 171-182).

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.