Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science. Degree awarded with distinction on 4 December 1996. Johannesburg 1996. / The problem with existing traffic light systems is that they are static and unable to respond to dynamic changes in traffic flow patterns. This report discusses an approach using distributed AI techniques to allow the control system to respond dynamically to the changes in the flow patterns. A simulated system (Datilis) has been developed, The design of the system is based on the assumption that maximising throughput at individual intersections will result in improved overall performance. The results generated and discussed in this report support this hypothesis.

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An intensive examination was conducted to test the credibility of current traffic signal change interval policies founded on a kinematic equation developed nearly 30 years ago. The investigation involved the review of relevant literature as well as an extensive collection of data. The literature review and data analysis revealed that current change interval policies rely on the disproven assumption that traffic decelerates at a constant rate. The data analysis also demonstrated that traffic approach speed and deceleration distance affect the manner in which deceleration occurs. Based on the data analysis, an alternative treatment of the kinematic equation is proposed using surrogate deceleration rates. The surrogate rates offer a pragmatic set of input for the kinematic equation. Therefore, rather than yielding a change interval based on an inaccurate assumption, agencies can implement change intervals which are responsive to local traffic.

International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The expectation-maximization (EM) algorithm is well established as a computationally efficient method for separable signal parameter estimation. Here, a new geometric derivation and interpretation of the EM algorithm is given that facilitates the understanding of its convergence properties. Geometric considerations then lead to an alternative separable signal parameter estimator based on successive cancellation. The new Generalized Successive Interference Cancellation (GSIC) algorithm may offer better performance than EM in the presence of large signal power disparities. Finally, application of the GSIC algorithm to CDMA-based radiolocation is discussed, and simulation results are presented.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

Traditional scholarship on the media effects of government activity focuses on the transfer of salience. Salience and priorities are conceptually distinct, although they are often incorrectly used interchangeably. Whereas salience refers to issue attention, priority pertains to issue preferences or importance. This paper offers that media effects are better understood as signals comprised of issue salience and importance in an environment characterized by variation in uncertainty and ambiguity. Using newspaper stories and congressional hearings datasets, unique measures are developed that incorporate the uncertainty and ambiguity of the information environment. The relationship between media signals and government problem prioritization is then examined. This research is important in situating media signaling within the context of the larger issue agenda, and helps to illuminate linkages between the public and government agendas. / text

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