969 resultados para Chemical Methods.


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Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

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Mode of access: Internet.

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"Contract AT(30-1)-2789."

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"A revised edition of Dr. F. Böckmann̓s Chemisch-technische Untersuchungsmethoden, edited by Professor G. Lunge, was published in 1899 ... practically a new work ... adapted to modern methods of work. In 1904 a second edition was called for, in which the whole of the subject matter was thoroughly revised and brought up to date ... The English translation has been made from the second German edition ... A bibliography ... is appended to each section, and all important tables, in addition to having printed in the text, are also printed for reference at the end of each volume."-Pref.

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Bibliographical footnotes. Bibliography: p. 360.

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Prepared for the Bureau of Land Management, under Contract YA-512-CT8-116, Washington State University, Pullman.

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Bibliography at end of each chapter except three.

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"In the present work there have been incorporated several papers ... which have been read before the Institution of Civil Engineers; and also the author's articles on 'Stoves' and 'Ventilation,' published in the Encyclopædia metropolitana."--Pref.

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Previous editions edited by W. W. Scott.