Heat transfer in canned particulate system in Newtonian and non-Newtonian liquids was studied during end-over-end agitation thermal processing in a pilot scale rotary retort. Computational methods for conventional overall heat transfer coefficient (U) and fluid to particle heat transfer coefficient (hfp) were found unsuitable in high viscosity fluids. A methodology for evaluating an apparent heat transfer coefficient (hap) between retort medium and particle, and an apparent overall heat transfer coefficient Ua between retort medium and can fluid was proposed. Use of h ap and Ua concepts permitted direct predictions of particle temperature and lethality based on retort temperature. / An L-16 orthogonal experimental design of experiments was carried out to select system factors that significantly affected hap and U a values for particles in high viscosity non-Newtonian and Newtonian fluids. Experiments using central composite rotatable design and full factorial design were carried out to study the effects of selected significant factors on hap and Ua. / Using all data obtained, dimensionless correlations were developed for the prediction of hap and Ua values. The developed correlations showed a good agreement with the experimental data. More precise predictions were achieved with trained artificial neural network (ANN) models. The results of ANN models could be compiled using algebraic equations and were included so that hap and Ua values could be predicted without actually using the ANN software. A flow visualization study was conducted to better understand the heat transfer behavior in high viscosity fluids. Results showed that in particulate high viscosity fluids, the particle liquid relative movement was very weak, implying that the heat transfer between them could converge to conduction-conduction rather than convection-conduction, which results in erroneous and unusually large hfp values.

Digital Elevation Models have been in use for more than three decades and have become a major component of geographic information processing. The intensive use of DEMs has given rise to many accuracy investigations. The accuracy estimate is usually given in a form of a global measure such as root-mean-square error (RMSE), mostly from a producer's point of view. Seldom are the errors described in terms of their spatial distribution or how the resolution of the DEM interacts with the variability of terrain. There is a wide range of topographic variation present in different terrain surfaces. Thus, in defining the accuracy of a DEM, one needs ultimately to know the global and local characteristics of the terrain and how the resolution interacts with them. In this thesis, DEMs of various resolutions (i.e., 10 arc-minutes, 5 arc-minutes, 2 km, 1 km, and 50 m) in the study area (Prince George, British Columbia) were compared to each other and their mismatches were examined. Based on the preliminary test results, some observations were made regarding the relations among the spatial distribution of DEM errors, DEM resolution and the roughness of terrain. A hypothesis was proposed that knowledge of the landscape characteristics might provide some insights into the nature of the inherent error (or uncertainty) in a DEM. To test this statistically, the global characteristics of the study area surfaces were first examined by measures such as grain and those derived from spectral analysis, nested analysis of variance and fractal analysis of DEMs. Some important scale breaks were identified for each surface and this information on the surface global characteristics was then used to guide the selection of the moving window sizes for the extraction of the local roughness measures. The spatial variation and complexity of various study area surfaces was characterized by means of seven local geomorphometric parameters. The local measures were extracted from DEMs with different resolutions and using different moving window sizes. Then the multivariate cluster analysis was used for automated terrain classification in which relatively homogeneous terrain types at different scale levels were identified. Several different variable groups were used in the cluster analysis and the different classification results were compared to each other and interpreted in relation to each roughness measure. Finally, the correlations between the DEM errors and each of the local roughness measures were examined and the variation of DEM errors within various terrain clusters resulting from multivariate classifications were statistically evaluated. The effectiveness of using different moving window sizes for the extraction of the local measures and the appropriateness of different variable groups for terrain classification were also evaluated. The major conclusion of this study is that knowledge of topographic characteristics does provide some insights into the nature of the inherent error (or uncertainty) in a DEM and can be useful for DEM error modelling. The measures of topographic complexity are related to the observed patterns of discrepancy between DEMs of differing resolution, but there are variations from case to case. Several patterns can be identified in terms of relation between DEM errors and the roughness of terrain. First of all, the DEM errors (or elevation differences) do show certain consistent correlations with each of the various local roughness variables. With most variables, the general pattern is that the higher the roughness measure, the more points with higher absolute elevation differences (i.e., horn-shaped scatter of points indicating heteroscedasticity). Further statistical test results indicate that various DEM errors in the study area do show significant variation between different clusters resulting from terrain classifications based on different variable groups and window sizes. Cluster analysis was considered successful in grouping the areas according to their overall roughness and useful in DEM error modelling. In general, the rougher the cluster, the larger the DEM error (measured with either the standard deviation of the elevation differences or the mean of the absolute elevation differences in each cluster). However, there is still some of the total variation of various DEM errors that could not be accounted for by the cluster structure derived from multivariate classification. This could be attributed to the random errors inherent in any of the DEMs and the errors introduced in the interpolation process. Another conclusion is that the multivariate approach to the classification of topographic surfaces for DEM error modelling is not necessarily more successful than using only a single roughness measure in characterizing the overall roughness of terrain. When comparing the DEM error modelling results for surfaces with different global characteristics, the size of the moving window used in geomorphometric parameter abstraction also has certain impact on the modelling results. It shows that some understanding of the global characteristics of the surface is useful in the selection of appropriate/optimal window sizes for the extraction of local measures for DEM error modelling. Finally, directions for further research are suggested.

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Aim: This study appraised the CQI mechanisms and processes in the clinical nursing divisions of five selected teaching hospitals located in South-West Nigeria and developed quality care indicators to measure and monitor quality of care amongst clinical based nurses in these teaching hospitals. Background: Studies have been done on evaluation of quality care to determine what good care is; whether the care nurses give is proper and effective, and whether the care provided is good quality. Several authors have asserted that evaluating the quality of nursing care is an essential part of professional accountability. Literature also suggests that in providing high quality care, it is important that nurses develop appropriate evaluative measurement tools to ensure professional aspect of nursing. Conversely, it is a concern that in the clinical nursing division of some teaching hospitals in SW Nigeria, CQI mechanisms/processes (such as a structured auditing, monitoring and measuring quality of nursing care, established systems of continuing professional learning/ In-service Education Unit) were not more evident, particularly when these teaching hospitals were supposed to be seen as models for providing quality care services. It was not certain what CQI activities were present in similar hospitals, and if such activities were present, there was uncertainty as to how these activities were performed. In addition, the type of instrument/tools available for nursing care measurement was uncertain. There is a paucity of published evidence relating to the quality of nursing care measurement in the teaching hospitals in SW Nigeria. Gaps identified in the study would form the basis for future training and education of nurses involved in care-giving to promote quality care. Findings from the study provided evidenced-based scientific rationale for practice in relation to quality nursing care measurement in the health care institutions, thus adding to the body of knowledge of quality improvement. The methodology employed in the study is an action research; with a mixed method-Sequential explanatory incorporated. Quantitative data was collected and analysed, followed by the collection and analyses of qualitative data. The study was done in five cycles which included a survey that elicited responses from the participants on general knowledge and perceptions about CQI. Cycle two included generating promising solutions and an action plan. In cycle three, established quality-care indicators were analysed, developed and thereafter, the newly adapted instrument for nursing care measurement was tested for applicability to settings. Participants reflected on the testing of the new tool in the fourth cycle and lastly, implementation/testing outcomes were evaluated in the fifth cycle. Conclusion: Established quality-care indicators were adapted in each of the five hospital settings for quality nursing care measurement. The newly adapted quality care indicators were tested for applicability on two acute-care wards in three of the five participating hospitals. The results of the study could be used in Nigeria and elsewhere as a means to protect the rights of the patient; by measuring and monitoring the quality of nursing care. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2009.