Ever since Halley (1686) superimposed onto a map of land forms. the direction of trade winds and monsoons between and near the tropics and attempted to assign them a physical cause. homo-sapiens has attempted to develop procedures which quantify the level of change in a spatial process. or assess the relationship between associated spatially measured variables. Most spatial data. whether it be originally point. linear or areal in nature. can be converted by a suitable procedure into a continuous form and plotted as an isarithmic map i.e. points of equal height are joined. Once in that form it may be regarded as a statistical surface in which height varies over area in much the same way as the terrain varies on topographic maps. Particularly in environmental statistics. the underlying shape of the surface is unknown. and hence the use of non-parametric techniques is wholly appropriate. For most applications. the location of data points is beyond the control of the map-maker hence the analyst must cope with irregularly spaced data points. A variety of possible techniques for describing a surface are given in chapter two, with attention focusing on the methodology surrounding kernel density estimation. Once a surface has been produced to describe a set of data. a decision concerning the number of contours and how they should be selected has to be taken. When comparing two sets of data. it is imperative that the contours selected are chosen using the same criteria. A data based procedure is developed in chapter three which ensures comparability of the surfaces and hence spurious conclusions are not reached as a result of inconsistencies between surfaces. Contained within this chapter is a discussion of issues which relate to other aspects of how a contour should be drawn to minimise the potential for inaccuracies in the swface fitting methodology. Chapter four focuses on a whole wealth of techniques which are currently available for comparing surfaces. These range from the simplest method of overlaying two maps and visually comparing them to more involved techniques which require intensive numerical computation. It is the formalisation of the former of these techniques which forms the basis of the methodology developed in the following two chapters to discern whether change/association has materialised between variables.One means of quantifying change between two surfaces, represented as a contoured surface, is in terms of the transformation which would be required for the two surfaces to be matched. Mathematically, transformations are described in terms of rotation, translation and scalar change. Chapter five provides a geometrical interpretation of the three transformations in terms of area, perimeter, orientation and the centre of gravity of the contour of interest and their associated properties. Although grid resolution is fundamentally a secondary level of smoothing, this aspect of surface fitting has generally been ignored. However to ensure consistency across surfaces, it is necessary to decide firstly, whether data sets of different sizes should be depicted using different mesh resolutions and secondly, how fine a resolution provides optimal results, both in terms of execution time and inherent surface variability. This aspect is examined with particular reference to the geometric descriptors used to quantify change. The question of random noise contained within a measurement process has been ignored in the analysis to this point. However in practice, some form of noise will always be contained within a process. Quantifying the level of noise attributable to a process can prove difficult since the scientist may be over optimistic in his evaluation of the noise level. In developing a suitable set of test statistics, four situations were examined, firstly when no noise was present and then for three levels of noise, the upper bounds of which were 5, 15 and 25%. Based on these statistics, a series of hypothesis tests were developed to look at the question of change for individual contour levels Le. local analysis. or alternatively for a whole surface by combining the statistics and effectively performing a multivariate test. A number of problems are associated with the methodology. These difficulties are discussed and various remedial measures are proposed. The theoretical derivation of the test statistic, both in the absence and presence of random noise, has proved mathematically to be extremely complex, with a number of stringent assumptions required to enable the theoretical distribution to be derived. A major simulation study was subsequently undertaken to develop the empirical probability distribution function for the various statistics defining change for the four levels of noise. Also for each of the statistics, the resultant power of the test was examined.The remaining chapter explicitly examines two case studies and how the methodology developed in the preceding two chapters may be implemented. The first example cited raises the question, 'Has a seasonal temperature change resulted during the fifty year span, 1930 to 1980, within the contiguous United States of America?' The data base was provided by the United States Historical Climatology Network (HCN) Serial Temperature and Precipitation Data, Quinlan et al (1987). The second problem examines whether there is an association between background radiation levels, within three regions of the south-west England, and the location of various fonns of leukaemia or whether case location is a product of the population distribution. Differences between this example and the previous illustration materialise in terms of the spatial resolution of the data; the leukaemia data are defined as punctual data points and are extremely sparse; the population distribution is defined as areal regions; with the radiation data being of a more continuous format. The methodology developed required modification, but aside of this a preliminary set of conclusions were reached.

published_or_final_version / abstract / toc / Ecology and Biodiversity / Doctoral / Doctor of Philosophy

The study compared electrical brain activity of subjects in five different conditions: eyes-closed at rest, eyes-open at rest, looking at a flashing object, looking at apparent movement, and looking at real movement. Absolute theta and alpha power in the frontal and occipital areas were analyzed. Significant differences were found in the frontal area. Results suggest that perceived movement requires higher order cognitive processes outside the occipital area. Implications for education and cognitive research are discussed.

Understanding water stress responses in maize and the genetic factors controlling these traits has direct application to breeding and genetic study. To understand water stress responses in more detail, this thesis characterizes a novel B73 ethyl methanesulfonate induced wilting maize mutant. This mutant is shown to express a wilting phenotype under both field and greenhouse conditions, exhibiting leaf roll, stunted stem growth and reduced fertility. Germination is unaffected in mutant seeds and no abnormal seedling phenotypes are observed. Onset of the phenotype is between V3 and V6 growth stage, and corresponds with a disruption of stem elongation. To characterize the genetic elements underlying the wilting phenotype, F2 and F3 mapping populations were phenotyped and genotyped. The mutant phenotype was found at variable frequencies between populations; ¼ or less of all mapping population members were observed as wilting, implicating a single genetic factor controlling the mutant phenotype. Background effects of the non-mutant parent and residual EMS mutations are hypothesized to be responsible for the unexpected frequency of wilting observed. Single nucleotide polymorphism and microsatellite markers localized the wilted mutant allele to a 7.4-Megabase region on the long arm of chromosome 7. The phenotype results and rough mapping data provide a base for further study and cloning of the mutant allele.

There are many different algorithms that have been shown to solve the simultaneous localization and mapping (SLAM) problem depending on the type of input data. Many of these algorithms use some form of cumulative current position as a state variable and only store landmarks in their globally mapped form, discarding past data. This thesis takes a different approach in not using current position as a cumulative state variable and storing and using past data. Landmarks are mapped relative to each other in their untransformed states and use either three points or one plane to maintain translation and rotation invariance. The Relative algorithms can use both current and past data for accuracy purposes. Using this approach, the SLAM problem is solved by data structures and algorithms rather than probabilistic modeling. The Relative algorithms are shown to be good solutions to the simulated SLAM problems tested in this thesis. In particular the Relative Point algorithm is shown to have a worst case computation complexity of O(nslogns). ns is the average quantity of points observed in a given observation and is not related to the total quantity of points on the map. The Relative Point algorithm is able to identify points with movement that is not correlated to the viewpoint at a low cost, and has comparable accuracy to a 6D no odometry Extended Kalman Filter.

This thesis introduces three different algorithmical and statistical strategies for the analysis of high-throughput sequencing data. First, we introduce a heuristic method based on enhanced suffix arrays to map short sequences to larger reference genomes. The algorithm builds on the idea of an error-tolerant traversal of the suffix array for the reference genome in conjunction with the concept of matching statistics introduced by Chang and a bitvector based alignment algorithm proposed by Myers. The algorithm supports paired-end and mate-pair alignments and the implementation offers methods for primer detection, primer and poly-A trimming. In our own benchmarks as well as independent bench- marks this tool outcompetes other currently available tools with respect to sensitivity and specificity in simulated and real data sets for a large number of sequencing protocols. Second, we introduce a novel dynamic programming algorithm for the spliced alignment problem. The advantage of this algorithm is its capability to not only detect co-linear splice events, i.e. local splice events on the same genomic strand, but also circular and other non-collinear splice events. This succinct and simple algorithm handles all these cases at the same time with a high accuracy. While it is at par with other state- of-the-art methods for collinear splice events, it outcompetes other tools for many non-collinear splice events. The application of this method to publically available sequencing data led to the identification of a novel isoform of the tumor suppressor gene p53. Since this gene is one of the best studied genes in the human genome, this finding is quite remarkable and suggests that the application of our algorithm could help to identify a plethora of novel isoforms and genes. Third, we present a data adaptive method to call single nucleotide variations (SNVs) from aligned high-throughput sequencing reads. We demonstrate that our method based on empirical log-likelihoods automatically adjusts to the quality of a sequencing experiment and thus renders a \"decision\" on when to call an SNV. In our simulations this method is at par with current state-of-the-art tools. Finally, we present biological results that have been obtained using the special features of the presented alignment algorithm. / Diese Arbeit stellt drei verschiedene algorithmische und statistische Strategien für die Analyse von Hochdurchsatz-Sequenzierungsdaten vor. Zuerst führen wir eine auf enhanced Suffixarrays basierende heuristische Methode ein, die kurze Sequenzen mit grossen Genomen aligniert. Die Methode basiert auf der Idee einer fehlertoleranten Traversierung eines Suffixarrays für Referenzgenome in Verbindung mit dem Konzept der Matching-Statistik von Chang und einem auf Bitvektoren basierenden Alignmentalgorithmus von Myers. Die vorgestellte Methode unterstützt Paired-End und Mate-Pair Alignments, bietet Methoden zur Erkennung von Primersequenzen und zum trimmen von Poly-A-Signalen an. Auch in unabhängigen Benchmarks zeichnet sich das Verfahren durch hohe Sensitivität und Spezifität in simulierten und realen Datensätzen aus. Für eine große Anzahl von Sequenzierungsprotokollen erzielt es bessere Ergebnisse als andere bekannte Short-Read Alignmentprogramme. Zweitens stellen wir einen auf dynamischer Programmierung basierenden Algorithmus für das spliced alignment problem vor. Der Vorteil dieses Algorithmus ist seine Fähigkeit, nicht nur kollineare Spleiß- Ereignisse, d.h. Spleiß-Ereignisse auf dem gleichen genomischen Strang, sondern auch zirkuläre und andere nicht-kollineare Spleiß-Ereignisse zu identifizieren. Das Verfahren zeichnet sich durch eine hohe Genauigkeit aus: während es bei der Erkennung kollinearer Spleiß-Varianten vergleichbare Ergebnisse mit anderen Methoden erzielt, schlägt es die Wettbewerber mit Blick auf Sensitivität und Spezifität bei der Vorhersage nicht-kollinearer Spleißvarianten. Die Anwendung dieses Algorithmus führte zur Identifikation neuer Isoformen. In unserer Publikation berichten wir über eine neue Isoform des Tumorsuppressorgens p53. Da dieses Gen eines der am besten untersuchten Gene des menschlichen Genoms ist, könnte die Anwendung unseres Algorithmus helfen, eine Vielzahl weiterer Isoformen bei weniger prominenten Genen zu identifizieren. Drittens stellen wir ein datenadaptives Modell zur Identifikation von Single Nucleotide Variations (SNVs) vor. In unserer Arbeit zeigen wir, dass sich unser auf empirischen log-likelihoods basierendes Modell automatisch an die Qualität der Sequenzierungsexperimente anpasst und eine \"Entscheidung\" darüber trifft, welche potentiellen Variationen als SNVs zu klassifizieren sind. In unseren Simulationen ist diese Methode auf Augenhöhe mit aktuell eingesetzten Verfahren. Schließlich stellen wir eine Auswahl biologischer Ergebnisse vor, die mit den Besonderheiten der präsentierten Alignmentverfahren in Zusammenhang stehen.

The primary goal of this research was the facilitation of cross-cultural communication between local Anishinaabe and settler communities within the context of the Rat Portage Common Ground Conservation Organization. Through the course of this study a combination of western cartographic conventions, phenomenological principles, and cultural asset mapping techniques have been applied. The original data discussed are the aggregation of three separate data collection initiatives. Each initiatives' individual results have been utilized in various ways to record, communicate, and verify the final research process and products. The research also sought to gain insight into the application of particular mapping methodologies to a phenomenological inquiry. The phenomenon under investigation was the place-based Anishinaabe cultural landscapes of the Common Ground Lands. While the employed mapping conventions were found to assist in realizing the phenomenological objectives of the research, it was also observed that phenomenology itself offered valuable insights into the act of mapping.

There are many different algorithms that have been shown to solve the simultaneous localization and mapping (SLAM) problem depending on the type of input data. Many of these algorithms use some form of cumulative current position as a state variable and only store landmarks in their globally mapped form, discarding past data. This thesis takes a different approach in not using current position as a cumulative state variable and storing and using past data. Landmarks are mapped relative to each other in their untransformed states and use either three points or one plane to maintain translation and rotation invariance. The Relative algorithms can use both current and past data for accuracy purposes. Using this approach, the SLAM problem is solved by data structures and algorithms rather than probabilistic modeling. The Relative algorithms are shown to be good solutions to the simulated SLAM problems tested in this thesis. In particular the Relative Point algorithm is shown to have a worst case computation complexity of O(nslogns). ns is the average quantity of points observed in a given observation and is not related to the total quantity of points on the map. The Relative Point algorithm is able to identify points with movement that is not correlated to the viewpoint at a low cost, and has comparable accuracy to a 6D no odometry Extended Kalman Filter.

No description available.

No description available.