Capstan drive transport system for motion picture film

The work presented describes the development of a capstan drive system for the transport of motion picture film. From a model description of the plant and computer aided system design analysis, control algorithms are formulated. The work shows how these relativity complex control algorithms are implemented by making use of the parallel processing capabilities of the transputer. A critical investigation of current film transport methods is undertaken leading to the design and testing of a prototype capstan drive mechanism. The capstan drive system is shown to eliminate problems of sprocket drives and their associated mechanisms. A multi-input multi-output controller is presented using state-space methods of design. The developed control strategies are fully tested on a model of the plant before hardware testing. The control outputs of the system are speed and tension. The final control solution is shown to be a combination of full-state feedback, integral control, and a Kalman filter estimator for the elimination of system disturbances. The transputer implementation of the developed control strategies is presented together with a comparison between simulation and experimental results. It is shown that computational times can be reduced by using multiple transputers and placing computation-intensive sections of the control algorithm on separate processors. Transputer configurations and interconnections are shown. The capstan system has been shown to allow faster printing speeds with improved transport accuracy leading to better quality of the final picture print. The system has been shown to be 'robust' to external disturbances and changes in plant parameters

Tailor-made tests for goodness of fit to semiparametric hypotheses

We introduce a new framework for constructing tests of general semiparametric hypotheses which have nontrivial power on the $n^{-1/2}$ scale in every direction, and can be tailored to put substantial power on alternatives of importance. The approach is based on combining test statistics based on stochastic processes of score statistics with bootstrap critical values.Comment: Published at http://dx.doi.org/10.1214/009053606000000137 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Household gasoline demand in the United States

Continuing rapid growth in U.S. gasoline consumption threatens to exacerbate environmental and congestion problems. We use flexible semiparametric and nonparametric methods to guide analysis of household gasoline consumption, and including this variable cuts the estimated income elasticity in half. Slower projected future growth in licensed drivers points to slower growth in gasoline consumption. A parsimonious representation of age, income, lifecycle and location effects is developed and tested. We show how flexible methods also helped reveal fundamental problems with the available price data.Supported by the MIT Center for Energy and Environmental Policy Research, the U.S. Dept. of Energy and the National Science Foundation

Censored Regressors and Expansion Bias

We show how using censored regressors leads to expansion bias, or estimated effects that are proportionally too large. We show the necessity of this effect in bivariate regression and illustrate the bias using results for normal regressors. We study the bias when there is a censored regressor among many regressors, and we note how censoring can work to undo errors-in-variables bias. We discuss several approaches to correcting expansion bias. We illustrate the concepts by considering how censored regressors can arise in the analysis of wealth effects on consumption, and on peer effects in productivity

A regression test of semiparametric index model specification

This paper presents a simple regression test of parametric and semiparametric index models against more general semiparametric and nonparametric alternative models. The test is based on the regression coefficient of the restricted model residuals on the fitted values of the more general model. A goodness-of-fit interpretation is given to the regression coefficient, where the variance of the coefficient is adjusted for the use of nonparametric estimators. An asymptotic theory is developed for the situation where kernel estimators are used to estimate unknown regression functions, and the variance adjustment terms are given for this case. The methods are applied to the empirical problem of characterizing environmental effects on housing prices in the Boston Housing data, where a partial index model is found to be preferable to a standard log-linear equation, yet not rejected against general nonparametric regression. Various issues in the asymptotic theory and other features of the test are discussed.Funded by a grant from the MIT Center for Energy and Environmental Policy Research

Semiparametric measurement of environmental effects

This paper gives the results of a semiparametric analysis of pollution effects on housing prices using the Boston Housing Data. The exposition introduces the basic ideas of modeling pollution impacts with hedonic price methods, discusses the standard log-linear model, and then introduces nonparametric estimation and semiparametric index models. We focus on the intuitive content and substantive results of the semiparametric analysis. We find that the impact of pollution is smaller than that previously estimated, and varies dramatically depending on the status level of the community. We give various interpretations of the findings, and contrast our methods with those used in previous analysis of the Boston Housing Data.Supported by the MIT Center for Energy and Environmental Policy Research

The prevalence of medical reasons for non-participation in the Scottish breast and bowel cancer screening programmes

Objective: Increasing uptake of cancer screening is a priority for health systems internationally, however, some patients may not attend because they are undergoing active treatment for the cancer of interest or have other medical reasons that mean participation would be inappropriate. This study aims to quantify the proportion of non-participants who have a medical reason for not attending cancer screening.<p></p> Methods: Medical reasons for not participating in breast and bowel screening were defined a priori on the basis of a literature review and expert opinion. The notes of 700 patients at two GP practices in Scotland were reviewed, to ascertain the prevalence of medical reasons amongst non-participants. Simple proportions and confidence intervals were calculated.<p></p> Results: 17.4% of breast and 2.3% of bowel screening non-participants had a medical reason to not participate. The two most common reasons were previous breast cancer follow up (8.86%) and recent mammogram (6.57%).<p></p> Conclusion: These patients may not benefit from screening while also being distressed by receiving an invitation. This issue also makes accurate monitoring and target-setting for improving uptake difficult. Further work is needed to estimate robustly the extent to which medical reasons account for screening non-participation in a larger population.<p></p&gt

Sources of productivity growth in the American coal industry

This paper develops new techniques to assess the expanse of the geographic market under varying supply and demand conditions and applies these techniques to the current wholesale electricity market in the western United States. This paper finds that, by and large, the expanse of the geographic market extends across most of the western United States, but that conditions which create congestion along transmission lines, such as high hydroelectric flows in the Pacific Northwest, transmission line outages and deratings, and high demand for wholesale electricity, cause the expanse of the geographic market to narrow at certain times.Supported by the MIT Center for Energy and Environmental Policy Research