Thesis (Ph. D.)--Virginia Polytechnic Institute, 1966. / Vita. Abstract. Includes bibliographical references (leaves 110-112). Also available via the Internet.

Thesis (Ph. D.)--Lehigh University, 1998. / Includes vita. Includes bibliographical references (leaves 137-138).

WiFi networks have become ubiquitous. However, due to the nature of the radio-wave medium, the performance of 802.11 is unpredictable and highly dependent on the environment. This problem is fundamental to 802.11's decentralized, signal-based airspace arbitration mechanism. When devices have incomplete and inconsistent channel conditions for an overlapping interference domain, their signals alone cannot ensure a fair competition for airspace. As a result, competing flows may suffer from unfair bandwidth distribution if the shared airspace is congested. A useful tool to visualize and diagnose problematic wireless networks is the set of devices interfering with each other at a given time. We say two devices a and b interfere when one of two possible situations occur. First, a is able to sense b's radio signals, though not necessarily decode them, resulting in a unable to send data. Second, a and b aren't in radio range, but their destination devices are, resulting in packet collisions. We call such a set of mutually interfering devices the interference neighbourhood. We present wypy, an online system which merges trace-files and produces a map of interfering devices contained within the trace. wypy is able to identify pairs of devices exhibiting either hidden or exposed terminal interference using a pipeline that consists of trace merging and reconstruction, filtering of simultaneously sending devices, throughput and delay signal calculations, and a test for interference correlation. We evaluate wypy using an in-lab testbed set up in known interference scenarios. / Science, Faculty of / Computer Science, Department of / Graduate

Time Series of water quality variables typically possess many of several characteristics which complicate analysis. Of interest to researchers is often the trend over time of the water quality variable. However, sometimes water quality variable levels appear to increase or decrease monotonically for a period of time then switch direction after some intervention affects the factors which have a causal relationship with the level of the variable. Naturally, when analyzed for trend as a whole, these time series usually do not provide significant results. The problem of testing for a change in trend is addressed, and a method for perfoming this test based on a test of equivalence of two modified Kendall's Tau nonparametric correlation coefficients (neither necessarily equal to zero) is presented. The test is made valid for use with serially correlated data by use of a new bootstrap method titled the effective sample size bootstrap. Further issues involved in applying this test to water quality variables are also addressed. / Ph. D.

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Correlation-based translated-feature finding techniques are fast and effective in identifying targets in test images despite unknown translation. Information involving both translation and in-plane orientation of targets, however, is important in many industrial machine vision applications such as manufacturing and quality assurance. A traditional correlation based technique that expands the search criteria to include in-plane orientation is based upon use of a bank of filters that each implement a feature finding operation for one rotation of the target. This computational complexity of this approach is inversely proportional to the resolution of the orientation estimate. This thesis develops a correlation based method for translation and in-plane orientation feature finding that requires only two underlying correlation filter operations. A composite filter is constructed from a specially arranged and complex weighted sum of the set of the translated exemplar filters contained the usual filter bank. The arrangement allows for robust peak location detection yielding the target position and the multiplier angle that is extracted from the amplitude of the peak output response supplys an orientation estimate. A demonstration system using two such filters in an iterative fashion to counteract different sources of interference produced results accurate to plus or minus 1 degree 100 times faster than the traditional system.

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