The construction of telescope systems with large apertures (≃10 meters) is currently being planned. These entire telescope systems should be optically tested in a double-pass configuration. The high cost of manufacturing optical flats large enough to test a large telescope has stimulated research on a new type of testing in which several smaller flats, or subapertures, are distributed over the telescope aperture. The problem is to combine the partial data obtained only over the subapertures in order to obtain the wavefront over the entire aperture. It was the purpose of this dissertation to prove experimentally that subaperture testing is feasible. The question of the necessity of phasing the subapertures relative to each other was specifically addressed in the experiment. A brief review is given of two algorithms utilizing Zernike polynomials. A third subaperture testing analysis algorithm, the Stuhlinger method, is developed in this work; this provides raw phase data over the entire aperture of the system under test. A statistical analysis of this algorithm is given. A 6 in. diameter array of seven subapertures was used in this small-scale test. Data were obtained with the array, a monolithic flat, and a mask simulating the array placed over the monolithic flat. The results of the experiment are in good agreement with control data measured with a Zygo interferometer. Data and analysis for the Stuhlinger method are also presented. Error analysis shows that Zernike coefficients derived using subaperture testing are 5 times less accurate than those derived using monolithic testing for the subaperture configuration used here. It is shown that knowledge of the subaperture tilts can produce accurate wavefront information with as few as 30 data points per subaperture, as compared with 750 data points per subaperture if tilts are unknown. In conclusion, subaperture testing indeed functions in the absence of subaperture phasing. Tilt information influences mostly the lower order Zernike coefficients; lack of such information may be compensated by the use of more data points. Algorithms yielding either Zernike coefficients or raw phase data were shown to function. (Abstract shortened with permission of author.)

In order to gain a better understanding of this microorganismand its role in human pathogenesis, a physical map of Moraxella catarrhalis type strain ATCC25238 was constructed using pulsed field gel electrophoresis (PFGE) in combination with Southern hybridization techniques. Restriction endonucleases Not I, Rsr II, and Sma I were used to digest the chromosomal DNA. An overlapping circular map was generated by cross-hybridization of isolated radiolabeled fragments of Moraxella catarrhalis genomic DNA to dried PFGE gels. The number and location of the 16S and 23S ribosomal RNA genes were determined by digestion with l-Ceul enzyme and by Southern hybridization. Virulence-associated genes, the gene for β-lactamase, and housekeeping genes were also placed onto the physical map.

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This study examines the communication role of profile perspective maps. This three dimensional map has the role of displaying comparatively simple models of spatial information. The elements of design used to portray profiles are hypothesized to influence map perception. Two of these variables: profile type and rotation are selected for study. Map data are represented in profile maps as a series of stepped or smooth profiles. Smooth profiles portray spatial trends of distributions better than stepped profiles. Bar scales accompany profiles to derive more accurate estimations of profile magnitude. Stepped profiles are more conducive for using bar scales to derive correct estimations of magnitude of the distribution. Rotation is used to present a spatial distribution in a series of maps at different azimuths as three dimensional mapping entails some amount of hidden views. The probability of correct recognition of congruency between profile maps, and detection of azimuth direction depends on the azimuth used, and complexity of the distribution. The number of cartography classes, work experience with maps, and class level did not have significant influence on perception of profiles. Academic major of the subjects was the only significant variable to influence the interpretation of profile maps. / Master of Science / incomplete_metadata

It is generally assumed that increased map precision (ie map unit homogeneity) and map purity (map unit accuracy) should result from increasing the scale of mapping of the soil resource, since it should enable a more intricate breakdown of the landscape into landform facet based units. This study compared the predictive success of a 1:1 OK scale soil association map with the 1:25K and 1:1OOK scale soil landscape maps within the Birrigai area of the Paddy's river catchment, south west of Canberra, A.C.T. The 1:25K and the 1:100K scale soil landscape maps were also evaluated in a second larger evaluation area in the Paddy's river catchment which allowed more of the larger soil landscape map units to be evaluated. The 1:25K scale soil map was produced by another author for the A.C.T Government, and was surveyed at a substantially lower survey intensity than that for the 1:100K and 1:10K scale soil maps (ie only 0.05 observation sites / cm2 of published map). These maps were evaluated using a set of randomly located independent evaluation sites in each evaluation area, and from these calculating and comparing standard Marsman & de Gruijter(1986) measures of Map Purity. The strength of soil-landscape relationships within this catchment were determined from a Fixed One Way Analysis of Variance, and from more simplistic graphical comparisons of the means and standard deviations of the discrete soil data within these landform based map units. Soil-landscape relationships for the Nominal scale soil data (ie class type data) were evaluated by comparing the Marsman & de Gruijter(1986) Homogeneity index ratings among the soil map units. Intensive survey traverses were also carried out in selected soil landscapes to further evaluate the strength of soil landscapes present. The results revealed obvious improvements in map quality associated with increasing map scale from 1:100,000 to 1:10,000, and these included increases in the predictive success (Map Purity), reductions in the extent of map unit impurities, and planning advantages associated with having individual land facets delineated on the 1:10,000 scale map. The respectable purity ratings achieved by the 1:100,000 scale soil landscape map (ie average purity rating of 63%) was largely attributed to the flexibility of the "soil material" approach to soil landscape mapping. The relatively poor performance of the 1:25K consultancy soil landscape map demonstrated the fact that; any benefit gained from the improved intricacy in the representation of map unit delineation's with increased mapping scale, will be drastically reduced if it is not matched by an associated increase in the intensity of field investigations. Evaluations of the soil-landscape relationships found that the land facets of the Paddy's river catchment generally failed to delineate areas that were both uniform and unique in respect of their soil properties. Soil-landscape relationships were instead found to be quite complex, applying to only certain land facets, and in regards to only certain soil properties. Soil maps with units based on landsurface features were recommended on the basis of the importance of other landscape factors other than soils to land capability ratings, as well as on the useability of such maps. This study recommended the adoption of a " >2 detailed soil profile observations / land facet in each map unit " mapping standard to ensure a reasonable estimate of the variability and modal soil conditions present, as well as a reliable confirmation of the perceived soil-landscape relationships. The error usually associated with small scale mapping was effectively reduced by rapid ground truthing, involving driving along the major roads dissecting the map area and making brief observations of soil exposures on road batters, despite the bias of the road network making such mapping improvements uneven across the map. The major point to come from this study was the re-emphasising of the point that soil spatial variability has to be accepted as a "real landscape attribute" which needs to be accurately described and communicated to land users, and must not be considered as some sort of soil mapping failure. The fact that individual facets of the landscape rarely coincide with unique pockets of uniform and unique soils and soil properties must be considered simply an on the ground reality of nature, and not some mapping failure. It was thought that since other landscape factors (eg hillslope gradient) most often dominate the determination of land use suitability and capability, it is better to effectively describe the range and modal state of the soil conditions within such facets, then to attempt to extrapolate possible soil boundaries using geostatistical techniques which cut across such land facets, and may or may not correlate with real groupings of soil properties, depending on the spatial resolution of the soil variability distribution in the landscape. Even so the results of this investigation do put the validity of the physiographic terrain class mapping model as a predictor of soil traits under question, at least for the more complex landscape settings.

This diploma thesis deals with the analysis of concept, mind maps and their other forms. The aim is to distinguish concept and mind maps. The other objectives are to create a set of these maps and to verify them in the teaching of physics course on second stage of secondary schools.

No description available.

Throughout history floods have been part of the human experience. They are recurring phenomena that form a necessary and enduring feature of all river basin and lowland coastal systems. In an average year, they benefit millions of people who depend on them. In the more developed countries, major floods can be the largest cause of economic losses from natural disasters, and are also a major cause of disaster-related deaths in the less developed countries. Flood disaster mitigation research was conducted to determine how remotely sensed data can effectively be used to produce accurate flood plain maps (FPMs), and to identify/quantify the sources of error associated with such data. Differences were analyzed between flood maps produced by an automated remote sensing analysis tailored to the available satellite remote sensing datasets (rFPM), the 100-year flooded areas "predicted" by the Flood Insurance Rate Maps, and FPMs based on DEM and hydrological data (aFPM). Landuse/landcover was also examined to determine its influence on rFPM errors. These errors were identified and the results were integrated in a GIS to minimize landuse / landcover effects. Two substantial flood events were analyzed. These events were selected because of their similar characteristics (i.e., the existence of FIRM or Q3 data; flood data which included flood peaks, rating curves, and flood profiles; and DEM and remote sensing imagery.) Automatic feature extraction was determined to be an important component for successful flood analysis. A process network, in conjunction with domain specific information, was used to map raw remotely sensed data onto a representation that is more compatible with a GIS data model. From a practical point of view, rFPM provides a way to automatically match existing data models to the type of remote sensing data available for each event under investigation. Overall, results showed how remote sensing could contribute to the complex problem of flood management by providing an efficient way to revise the National Flood Insurance Program maps.