Thesis (M.Ag.Sc.) University of Adelaide, Dept. of Agriculture,1980.

Habilitationsschrift--Universität Fridericiana Karlsruhe. / At head of title: IFO-Institut für Wirtschaftsforschung. Bibliography: p. [133]-137.

Habilitationsschrift--Universität Fridericiana Karlsruhe. / At head of title: IFO-Institut für Wirtschaftsforschung. Bibliography: p. [133]-137.

Thesis (M.S.)--University of Wisconsin--Madison. / Typescript. eContent provider-neutral record in process. Description based on print version record.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 348-353).

A series of six consecutive input-output tables has been constructed for the economy of West Malaysia for the period from 1960 to 1965. This thesis provides an evaluation of their efficiency when applied in forecasting intermediate output. A brief review of the theoretical structure of the static input-output model developed by Leontief has been presented. Particular attention has been given to the economic assumptions which are necessary to make the prediction procedure tenable. The basic assumption of constant input coefficients was not tested directly, however. Instead, the empirical usefulness of the input-output system has been evaluated in terms of the quality of predictions it yields. Each of the tables from 1960 to 1964 has been used in turn to predict intermediate sectoral outputs for succeeding years to 1965. Input-output prediction errors were calculated by reference to the observed intermediate outputs set forth in the tables. To test the significance of these errors, a comparison was made with the errors that arose when corresponding projections of intermediate output were made from a naive extrapolation model. In addition the overall effect on the input-output predictions of the length of the forecast period was analyzed and the relative performance of individual sectors was examined. Wherever possible, the efficiency of the West Malaysian tables was compared with that of input-output tables for the Netherlands economy. In general the predictive power of the West Malaysian tables was not impressive. On the average the input-output forecasts proved to be superior to the naive extrapolations only when the prediction period did not exceed two years. For individual sectoral forecasts, the input-output model yielded better predictions of intermediate output in only seven of the 15 sectors considered. In every comparison with the efficiency of the Netherlands tables, the inferiority of the West Malaysian tables was demonstrated. Attempts have been made in the thesis to trace the reasons for the poor performance. Some improvements to the tables have been suggested. / Arts, Faculty of / Vancouver School of Economics / Graduate

This thesis is concerned with aspects of a theory of machine perception. It is shown that a comprehensive theory is emerging from research in computer vision, natural language understanding, cognitive psychology, and Artificial Intelligence programming language technology. A number of aspects of machine perception are characterized. Perception is a recognition process which composes new descriptions of sensory experience in terms of stored stereotypical knowledge of the world. Perception requires both a schema-based formalism for the representation of knowledge and a model of the processes necessary for performing search and deduction on that representation. As an approach towards the development of a theory of machine perception, a computational model of recognition is presented. The similarity of the model to formal mechanisms in parsing theory is discussed. The recognition model integrates top-down, hypothesis-driven search with bottom-up, data-driven search in hierarchical schemata representations. Heuristic procedural methods are associated with particular schemata as models to guide their recognition. Multiple methods may be applied concurrently in both top-down and bottom-up search modes. The implementation of the recognition model as an Artificial Intelligence programming language called MAYA is described. MAYA is a multiprocessing dialect of LISP that provides data structures for representing schemata networks and control structures for integrating top-down and bottom-up processing. A characteristic example from scene analysis, written in MAYA, is presented to illustrate the operation of the model and the utility of the programming language. A programming reference manual for MAYA is included. Finally, applications for both the recognition model and MAYA are discussed and some premising directions for future research proposed. / Science, Faculty of / Computer Science, Department of / Graduate

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Thesis (Ph. D.)--University of Pennsylvania, 1995. / Includes bibliographical references (leaves 293-303).

A healthy diet is related to a low risk of chronic diseases. A large body of research is devoted to improving social welfare by promoting healthy eating. This dissertation addresses the relation of food and health by analyzing the money and time inputs in food, the food poverty measurement, and a corresponding health outcome. The second chapter extends the current food poverty measure in headcount and proposes a set of Foster, Greer, and Thorbecke (FGT) indices, which is commonly used in development literature, in food poverty to allow for a more comprehensive understanding in food poverty evaluation. The counter-factual analysis on removing the American Recovery and Reinvestment Act (ARRA) component from the food expenditure shows that the original metrics underestimate the reduction to food expenditure poverty associated with ARRA, whereas the FGT indices indicate a slightly larger impact of ARRA in alleviating food poverty. The third chapter uses the same FGT indices in food poverty measurement but focuses on the sensitivity of these measurements to a different spatial and temporary food price. We use linear regression to estimate the local level of food poverty thresholds. The results show the spatial and temporal-specific thresholds are higher than the national threshold. The West region shows the most severe poverty situation, indicating the importance of considering spatial and temporal variations in measuring food expenditure poverty. The decompositions of food expenditures show that both the Supplemental Nutrition Assistance Program (SNAP) benefits and money spent on protein play an essential role in reducing food expenditure poverty. The fourth chapter combines the two datasets used in the previous two chapters to investigate the connection between the resources (money and time) devoted to food and a corresponding health outcome (Healthy Eating Index, HEI). Two-Sample-2-Stage-Least-Square (TS2SLS) model is used to account for the two different datasets in predicting the time spent on food-related activities. After obtaining the time input, a Three-Stage-Least-Square (3SLS) model shows the time input improves the HEI for Non-SNAP households, who are more constrained by time. The decomposition of the impact of education on the HEI shows the indirect impact account for 22% of the total impact. This analysis breaks down the impact of the characteristics on HEI through different channels, thus offers more comprehensive policy recommendations. / Doctor of Philosophy / A healthy diet is related to a low risk of chronic diseases. A large body of research is devoted to improving social welfare by promoting healthy eating. This dissertation is a series of studies on food and health regarding the money and time input on food, the food poverty measurement, and the corresponding health outcome. The second chapter extends the current food poverty measure in headcount and proposes a set of distributional metrics: depth and severity, which measures how far away households are away from the targeted threshold and how severe the food poverty is respectively. These distributional metrics allow for a more comprehensive understanding of food poverty evaluation. We also analyzed the change of the metrics when removing part of the food expenditure funding source. The analysis shows the original metrics tend to underestimate the reduction to food expenditure poverty and indicates a slightly larger impact of removed funding source in alleviating food poverty. The third chapter uses the same distributional food poverty metrics, but focuses on the sensitivity of these measurements to different spatial and temporal food prices. We use linear regression in estimating the local food poverty thresholds. The results show the spatial and temporal-specific thresholds are higher than the national threshold. The West region shows the most severe poverty situation, indicating the importance of considering spatial and temporal variations in measuring food expenditure poverty. The forth chapter combines the two datasets used in the previous two chapters to investigate the connection between the resources (money and time) spent on food and a corresponding health outcome. A special econometrics model is used to predict the time spent on food-related activities with two datasets. After obtaining the time input, a system of equations model shows the time input improves the healthy eating for households who are more constrained by time. The decomposition of the impact of education on healthy eating shows the indirect impact account for 22% of the total impact. This analysis breaks down the impact of the characteristics on HEI through different channels, thus offers more comprehensive policy recommendations.