The purpose of this paper is to introduce a method for identifying years of anomalous radial growth, which are called atypical years and are characterized by particularly narrow rings for certain trees or sites, and wide for the others. With this aim, we use principal components analysis (PCA) of tree -ring series, where years are the variables and trees or sites are the individuals, even though in classical dendrochronological applications of PCA, the trees or sites are considered as variables and the years as cases. The relevant method is explained and results are given for five cedar forests (Cedrus atlantica (Endl.) Carrière) in Morocco.

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This thesis documents the investigation into the acquisition of knowledge from biological data using computational methods for the discovery of significantly frequent patterns in gene location and phylogeny. Beginning with an initial statistical analysis of distribution of gene locations in the flowering plant Arabidopsis thaliana, we discover unexplained elements of order. The second area of this research looks into frequent patterns in the single dimensional linear structure of the physical locations of genes on the genome of Saccharomyces cerevisiae. This is an area of epigenetics which has, hitherto, attracted little attention. The frequent patterns are patterns of structure represented in Datalog, suitable for analyses using the logic programming methodology Prolog. This is used to find patterns in gene location with respect to various gene attributes such as molecular function and the distance between genes. Here we find significant frequent patterns in neighbouring pairs of genes. We also discover very significant patterns in the molecular function of genes separated by distances of between 5,000 and 20,000 base pairs. However, in complete contrast to the latter result, we find that the distribution of genes of molecular function within a local region of ±20, 000 base pairs is locationally independent. In the second part of this research we look for significantly frequent patterns of phylogenetic subtrees in a broad database of phylogenetic trees. Here we investigate the use of two types of frequent phylogenetic structures. Firstly, phylogenetic pairs are used to determine relationships between organisms. Secondly, phylogenetic triple structures are used to represent subtrees. Frequent subtree mining is then used to establish phylogenetic relationships with a high confidence between a small set of organisms. This exercise was invaluable to enable these procedures to be extended in future to encompass much larger sets of organisms. This research has revealed effective methods for the analysis of, and has discovered patterns of order in the locations of genes within genomes. Research into phylogenetic tree generation based on protein structure has discovered the requirements for an effective method to extract elements of phylogenetic information from a phylogenetic database and reconstruct a single consensus tree from that information. In this way it should be possible to produce a species tree of life with high degree of confidence and resolution.

Hypertension is a major risk factor for coronary artery disease, stroke, and kidney disease. Many studies suggest that elevated intramural stresses caused by hypertension may stimulate inflammatory changes, but little has been done to ascertain whether inflammation and stress are spatially correlated. Such correlations are a first step in identifying the mechanisms that may relate intramural stress to disease so that more effective clinical treatments may be developed. Arterial branches exhibit local stress peaks and are focal points for the onset of disease. They are thus a logical place to examine whether high stresses spatially correlate with increased inflammation. This research seeks to 1) develop a histology-based method to reconstruct small arterial branches; 2) use finite element analysis to evaluate intramural stresses where experimental testing is of limited use; 3) quantify biological measures of inflammation; and 4) visually and statistically compare the distribution of stress with the distribution of inflammation. Hypertension was induced in Sprague-Dawley rats by implanting Angiotensin II pumps for 7 days or 21 days. Normotensive rats were used as controls. To preserve morphology the mesentery was pressure-fixed in situ, harvested, processed, and embedded in glycol methacrylate resin. Branch geometry was reconstituted from serial sections. This involved: correcting deformations caused by sectioning; aligning sections into an image stack; identifying vessel boundaries; creating a surface suitable for finite element analysis; reducing the branch geometry to a midplane surface; and using Ansys (Ansys, Inc.) to mesh the midplane surface with a variable-thickness shell element. The pattern of inflammation was characterized by measuring the local density of monocytes and macrophages. Cell density was expressed as a distribution on the branch surface, which simplified visualization and facilitated statistical comparisons of inflammation with stress. Both intramural stresses and inflammation were greater near branches during hypertension. In most cases, however, high stresses and high cell density were not spatially collocated. The onset of an adaptive response may reduce the strength of this correlation. Maximal wall tension, defined as the maximal midplane stress multiplied by the wall thickness, was elevated near branches and strongly correlated with cell density.

Ranking and Selection procedures have been designed to select the best system from a number of alternatives, where the best system is defined by the given problem. The primary focus of this thesis is on experiments where the data are from simulated systems. In simulation ranking and selection procedures, four classes of comparison problems are typically encountered. We focus on two of them: Bernoulli and multinomial selection. Therefore, we wish to select the best system from a number of simulated alternatives where the best system is defined as either the one with the largest probability of success (Bernoulli selection) or the one with the greatest probability of being the best performer (multinomial selection). We focus on procedures that are sequential and use an indifference-zone formulation wherein the user specifies the smallest practical difference he wishes to detect between the best system and other contenders. We apply fully sequential procedures due to Kim and Nelson (2004) to Bernoulli data for terminating simulations, employing common random numbers. We find that significant savings in total observations can be realized for two to five systems when we wish to detect small differences between competing systems. We also study the multinomial selection problem. We offer a Monte Carlo simulation of the Bechhofer and Kulkarni (1984) MBK multinomial procedure and provide extended tables of results. In addition, we introduce a multi-factor extension of the MBK procedure. This procedure allows for multiple independent factors of interest to be tested simultaneously from one data source (e.g., one person will answer multiple independent surveys) with significant savings in total observations compared to the factors being tested in independent experiments (each survey is run with separate focus groups and results are combined after the experiment). Another multi-factor multinomial procedure is also introduced, which is an extension to the MBG procedure due to Bechhofer and Goldsman (1985, 1986). This procedure performs better that any other procedure to date for the multi-factor multinomial selection problem and should always be used whenever table values for the truncation point are available.

Botnets are collections of compromised machines which are controlled by a remotely located adversary. Botnets are of signi cant interest to cybersecurity researchers as they are a core mechanism that allows adversarial groups to gain control over large scale computing resources. Recent botnets have become increasingly complex, relying on Peer-to-Peer (P2P) protocols for botnet command and control (C&C). In this work, a packet-level simulation of a Kademlia-based P2P botnet is used in conjunction with a statistical analysis framework to investigate how measured botnet features change over time and across an ensemble of simulations. The simulation results include non-stationary and non-ergodic behaviours illustrating the complex nature of botnet operation and highlighting the need for rigorous statistical analysis as part of the engineering process. / Graduate / 0984, 0537, 0544

To properly analyze the advantages and disadvantages of voting rules, and how well the outcomes that they yield reflect voters' preferences, one needs very large data sets, since paradoxes that occur very rarely may have large impacts. Since such amounts of election data are currently unavailable, it is important to be able to use random procedures to generate data that have the same statistical characteristics as real election data. It is the purpose of this work to identify a statistical characterization of voting data, to empower researchers to use random procedures to generate data that is statistically indistinguishable from real voting data. / Ph. D.

When tones comprised of six octave-related harmonics are placed in pairs, where the two tones are separated by a tritone, some subjects perceive the direction of pitch change from the first to the second tone as ascending, while other subjects perceive it as descending. This is the basis for what is currently labeled the Tritone Paradox. The Tritone Paradox was investigated in a set of four experiments that made use of different experimental procedures that employed a 0-750 ms silent interval between tones in a trial-pair, different methods of stimulus presentation (i.e. open air or earphone) and 125 - 500 ms stimulus durations. Major emphasis was placed on the implementation of a standardized experimental procedure and the use of a standardized method of analyzing results in a Tritone Paradox experiment. To this end, an analysis method was designed using circular statistics, which resulted in a truly objective method of analyzing and classifying subjects while making use of all subject data. Analyses indicated that peak-pitch class was highly correlated with the angle of a mean vector (AMV) and that the depth of a profile was correlated with the length of a mean vector (LMV). The AMV and LMV may be combined to produce a single summary measure for a subject's performance. Two modes of responding employed by subjects were identified. Profiles generated using a spectral-envelope-controlled mode of responding are characterized by judgments of tones under one envelope being close to 180° out of phase with judgments made under a spectral envelope centered one half octave away from the other. Profiles generated using a pitch-class-controlled mode of responding are characterized by judgments of tones under one spectral envelope closely resembling judgments of tones made under a spectral envelope centered a tritone away from the first spectral envelope. Angular-Separation analysis details the difference between the AMV for two separate profiles generated by a subject. This analysis technique is a fast, reliable method for identifying individual differences in mode of responding between subjects. Angular-Separation analyses were used to verify the presence of 'spectral-envelope-controlled' subjects, which were first described in detail by Repp (1994). These subjects appeared in significant proportions in all conditions. Based on the results of these analyses, the traditional practice of using a single-averaged profile to describe a subject has been questioned. Such a profile does not adequately describe the performance of a subject using a spectral-envelope-controlled mode of responding. The single-averaged profile masks the differences between these subjects and those using a 'pitch-class-controlled' mode of responding, which are the subjects typically described in the literature. Results of the Angular-Separation analysis across Experiments 1 -4 showed similar proportions of subjects using a pitch-class-controlled or a spectral-envelope-controlled mode of responding. Evidence was found to indicate that the largest proportion of subjects using a pitch-class-controlled mode of responding was observed in an experimental condition that used 125-ms stimuli with no silent interval between tones in a pair. Evidence was also found to indicate that the largest proportion of subjects using a spectral-envelope-controlled mode of responding was observed in an experimental condition that employed 500 ms stimuli with a 500 ms silent interval between tones in a trial pair. It therefore appears that the duration of tones and the duration of a silent interval between tones in a trial pair will influence the mode of responding adopted by a subject in a Tritone Paradox experiment. The pure-tone pre-test, described in the literature as a subject selection tool, was investigated and results indicate that performance on such a pre-test does not predict how consistent a subject's performance will be in a Tritone Paradox task. Although mean LMV decreased as pre-test error scores increased, there was no significant correlation found between individual subjects' error scores and LMV values. This pretest, however, has some value in predicting some subjects' mode of responding. The vast majority of subjects with three or more errors on a pure-tone pre-test produced profiles that were classified as spectral-envelope controlled. These results suggest that the bulk of those subjects eliminated in past Tritone Paradox experiments that employed a pure-tone pre-test, may have been subjects who were far more likely to use a spectral-envelope controlled mode of responding. / Thesis / Doctor of Philosophy (PhD)

The mountainous western Virginia is the source of the headwater streams for the New, the Roanoke, and the James rivers. The region is prone to flash flooding, typically the result of localized precipitation. Fortunately, within the region, there is an efficient system of instruments for real-time data gathering with IFLOWS (Integrated Flood Observing and Warning System) gages, WSR-88D Doppler radar, and high precision GPS (Global Positioning System) receiver. The focus of this research is to combine the measurements from these various sensors in an algorithmic framework to determine the flash flood magnitude. It has been found that the trend in the GPS signals serves as a precursor for rain events with a lead-time of 30 minutes to 2 hours. The methodology proposed herein takes advantage of this lead-time as the trigger to initiate alert related calculations. It is shown here that the sum of the rates of change of total cloud water, water vapor contents and logarithmic profiles of partial pressure of dry air and temperature in an atmospheric column is equal to the rain rate. The total water content is measurable as the profiles of integrated precipitable water (IPW) from the GPS, the vertically integrated liquid (VIL) from the radar (representing different phases of the atmospheric water) and the pressure and temperature profiles are available. An example problem is presented illustrating the involving the calculations. / Master of Science

A principal components model for analyzing tree-ring data is presented which allows one to examine site heterogeneity and to compose chronologies of a new kind in a conceptually unified and computationally efficient manner. Using this model, one can develop chronologies that correlate better with local climate data than the standard chronology for a site and which can be tested for time stability within the framework of the model. The numerical procedures are described and applied to a specific tree site to illustrate their use and their usefulness. The tree-ring width data tested is from a white spruce (Picea glauca [Moench.] Voss) site in the forest-tundra ecotone of Yukon Territory. The results from the study of this and other sites indicate that more climatic information can be extracted using these techniques.