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The aim of this thesis was to examine environmental covariate-related issues, the resolution dependency, the contribution of vegetation covariates, and the use of LiDAR data, in the purposive sampling design for fuzzy logic-based digital soil mapping. In this design fuzzy c-means (FCM) clustering of environmental covariates was employed to determine proper sampling sites and assist soil survey and inference. Two subsets of the Laurel Creek Conservation area were examined for the purposes of exploring the resolution and vegetation issues, respectively. Both conventional and LiDAR-derived digital elevation models (DEMs) were used to derive terrain covariates, and a vegetation index calculated from remotely sensed data was employed as a vegetation covariate. A basic field survey was conducted in the study area. A validation experiment was performed in another area. The results show that the choices of optimal numbers of clusters shift with resolution aggregated, which leads to the variations in the optimal partition of environmental covariates space and the purposive sampling design. Combining vegetation covariates with terrain covariates produces different results from the use of only terrain covariates. The level of resolution dependency and the influence of adding vegetation covariates vary with DEM source. This study suggests that DEM resolution, vegetation, and DEM source bear significance to the purposive sampling design for fuzzy logic-based digital soil mapping. The interpretation of fuzzy membership values at sampled sites also indicates the associations between fuzzy clusters and soil series, which lends promise to the applicability of fuzzy logic-based digital soil mapping in areas where fieldwork and data are limited.

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The pattern of inactivation in the DXS8237E-UBE1-PCTK1 region is of particular interest, since the mechanisms of X chromosome inactivation and the escape from inactivation are, as yet, not fully understood. The inactivation status of the DXS8237E and PCTKl gene differ: the first undergoes normal inactivation and the second escapes this process. The status of the UBEl gene has been controversial, although it is widely excepted that it does escape X chromosome inactivation. Physical mapping of the region employing YACs and subsequently P ACs has been undertaken, but was restricted in scope by the high frequency of rearrangements occurring. DNA sequences between DXS8237E, UBE1, PCTKl and the distal gene, UHX1, have been investigated with regard to LINEI elements, which are thought to playa role in X-inactivation. The results obtained strongly suggest a link between LINE1 elements and X chromosome inactivation. Sequence analysis results also contributed to the understanding of difficulties with restriction mapping of the region. Further, this work includes the first reported establishment of the UBEl exonintron boundaries. Additionally, genomic sequence analysis showed that only 46kb separate DXS8237E from UHX1, which confirms that this region is extremely gene rich.

Doctor of Philosophy(PhD) / This thesis proposes the use of the augmented system form - a generalisation of the information form representing both observations and states. In conjunction with this, this thesis proposes a novel graph representation for the estimation problem together with a graph based linear direct solving algorithm. The augmented system form is a mathematical description of the estimation problem showing the states and observations. The augmented system form allows a more general range of factorisation orders among the observations and states, which is essential for constraints and is beneficial for sparsity and numerical reasons. The proposed graph structure is a novel sparse data structure providing more symmetric access and faster traversal and modification operations than the compressed-sparse-column (CSC) sparse matrix format. The graph structure was developed as a fundamental underlying structure for the formulation of sparse estimation problems. This graph-theoretic representation replaces conventional sparse matrix representations for the estimation states, observations and their interconnections. This thesis contributes a new implementation of the indefinite LDL factorisation algorithm based entirely in the graph structure. This direct solving algorithm was developed in order to exploit the above new approaches of this thesis. The factorisation operations consist of accessing adjacencies and modifying the graph edges. The developed solving algorithm demonstrates the significant differences in the form and approach of the graph-embedded algorithm compared to a conventional matrix implementation. The contributions proposed in this thesis improve estimation methods by providing novel mathematical data structures used to represent states, observations and the sparse links between them. These offer improved flexibility and capabilities which are exploited in the solving algorithm. The contributions constitute a new framework for the development of future online and incremental solving, data association and analysis algorithms for online, large scale localisation and mapping.

[Abstract]Agricultural crops exhibit within-field spatial variation. This variation partly results from relevant bio-physical and environmental factors that influence thecrop during the growing season. The plant integrates the effects of nutrition, water, pests and disease, and displays the results in the foliage. Remote sensing techniques allow the foliage to be monitored and the crop status to be assessed.While the use of conventional remote sensing systems has found many applications in agriculture, it is constrained by a number of issues and problems related to spatial resolution, repeat cycle, minimum area acquired, timeliness of data, etc. Thus, this research explores the potential of developing and assessing low-cost sensing technologies to overcome these limitations. The specificobjectives were to: a) identify, evaluate, and analyse the different options for a low-cost low-altitude (LCLA) remote sensing system that has potential for precision agriculture, b) develop a LCLA remote sensing system that is appropriate for use in mapping selected crop attributes (i.e. grain protein, yield, maturity and crop type), and c) evaluate the accuracy of classification and prediction of the cereal crop attributes.A low-cost sensor system was developed that incorporated two consumer digital still cameras. One camera captured the colour portion of the spectrum, while the other one (with the addition of a band-pass filter) captured the nearinfrared light. Both cameras were modified to be remotely triggered and externally powered. This sensor arrangement utilised 1.0 megapixel cameras in the earlier investigations and then 5.0 megapixel cameras in most recent missions. The sensors were equally well suited to mounting on a remotely controlled aircraft or suspended beneath a helium balloon.Various approaches were taken to determine and evaluate the relationships between imagery and crop attributes. Statistical methods included the use of correlation and discriminant function analysis, along with partial least squares regression. Image analysis techniques included the use of both pixel-based (supervised approach) and object-orientated (multi-resolution segmentation) classifications.The results showed that low-cost low-altitude remote sensing systems (incorporating consumer digital cameras with helium balloons or remotely controlled aircraft) have great capacity to quantify variability in cereal graincrops. Excellent relationships were found between the ‘at-harvest’ yield (R2=0.902) and protein content (R2=0.660) of wheat using a single image recorded at flowering. Partial least squares regression, using the crossvalidatedapproach, produced a stronger relationship with a prediction accuracy of 94.2% for yield and 88.5% for protein. This relationship exceeded all other studies reported in the literature.The same LCLA system has also accurately discriminated (using statistical methods) between: a) different nutrition levels in a wheat crop with 75.6% of the cases correctly classified, and b) between different cereal grain species (with differing nutrition levels) with 86.3% accuracy. These classification accuracies are comparable with, or exceeding other more expensive and/or complicated methods. Attempting to discriminate using image analysisprocedures, the pixel-based methods yielded an overall accuracy of 65.9% when classifying cereal grain crop species comprising of nine classes. When merged to six classes, the accuracy improved to 82.1%. Using an objectorientated approach has improved the overall accuracy to 81.0% for the ninecategory classification. This study also demonstrated LCLA’s ability to assessthe various growth stages of a barley crop prior to maturity with 83.5% of cases correctly classified.This study concluded that it is feasible to accurately assess selected cereal grain crop attributes using low-cost consumer technologies. The accuracies achievedusing this system were comparable with, or exceeded, other reported studies that used more complicated and expensive sampling systems. Further work is needed to continue refining the initial work on a fully autonomous unmannedaerial vehicle (UAV) started in the later part of this study, to extend the use of the LCLA system into broader scale applications.

The adoption of e-learning technologies in campus universities has not realised its potential for meeting the learning needs and expectations of 21st century students. By modelling university learning and teaching as a complex adaptive system, this thesis develops a new way of understanding and managing the adoption of new learning technologies in campus universities. The literature on learning and teaching in higher education indicates that lecturers??? ability to innovate in their teaching is constrained by tacit and discipline-specific educational knowledge. Introducing new methods and technologies into mainstream university teaching requires explicit review of educational knowledge, and requires support from departmental and institutional organizational systems. Research on organizational change in other contexts, such as manufacturing industry, has used complex adaptive systems modelling to understand the systemic interdependence of individual strategies, organizations and technologies. These models suggest that the integration of new e-learning technologies into mainstream campus university teaching will involve corresponding change processes. Part of this change requires the linking up of diverse disciplinary perspectives on learning and teaching. The thesis develops a conceptual framework for researching university learning and teaching as a complex adaptive system that includes learning technologies, people, and their organization within a university. Complex adaptive systems theory suggests that the capacity of a campus university to adapt to new e-learning technologies will be reflected in patterns in the strategies of those lecturers who are early adopters of those technologies. A context-specific study in the University of New South Wales used cognitive mapping to represent and analyse the strategies of a group of 19 early adopters of e-learning technology. These early adopters were participants in a cross-discipline Fellowship programme intended to develop their ability to act as change agents within the university. Analysis of the maps gathered before and after the Fellowship, triangulated with data on the Fellows??? participation in organizational change, leads to a new way of modelling how university learning and teaching systems, including their technologies, adapt within a complex and changing higher education context.

Bibliography: leaves 98-136 / viii, 152 leaves : ill ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Paediatrics, 1989

Corrections pasted behind title page. / Bibliography: leaves 294-341. / xi, 341, [42] leaves, [42] leaves of plates : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Involves the construction of a detailed physical map of the distal band of the long arm of human chromosome 16, 16q24. / Thesis (Ph.D.)--University of Adelaide, Dept. of Cytogenetics and Molecular Genetics, 1997

Errata slip inserted. / Bibliography: leaves 68-93. / viii, 93, [42] leaves, [15] leaves of plates : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Rye chromosome 6R in triticale contains a gene useful for resistance to cereal cyst nematode. This study shows that the complex structure of this chromosome may prevent render its use impracticle in introgression of this resistance into wheat. / Thesis (Ph.D.)--University of Adelaide, Dept. of Plant Science, 1998