5 results match your criteria: "University of California Southern[Affiliation]"

Development of an artificial intelligence expert system for diagnosing occupational lung disease requires explicit specification of the structure of knowledge necessary in clinical occupational medicine independent of the process by which the knowledge is utilized. Furthermore, explicit recognition of sources of uncertainty is necessary. Seven categories of knowledge define the diagnostic knowledge base in occupational pulmonary medicine.

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The relationship between the pattern of breathing in response to respirator-type loads and an individual's psychophysiologic sensitivity to loads (load scaling sensitivity, LSS) was investigated in the study of 11 normal volunteers. LSS was measured by having the subjects numerically rate a series of resistors; Steven's Psychophysical Law was used to evaluate sensitivity as the slope relating log (sensation) to log (stimulus). Peak pressure and actual added resistance were the stimuli.

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Performance of dust respirators with facial seal leaks: I. Experimental.

Am Ind Hyg Assoc J

October 1987

University of California Southern Occupational Health Center, UCLA School of Public Health 90024.

The ability of representative half-mask and single-use respirators with facial seal leaks to provide protection against aerosols was evaluated by experimental measurement. Respirators were mounted on a manikin in a test chamber and operated at seven steady flow rates over the range of 2 to 150 L/min. Samples of polydisperse and monodisperse aerosols were taken from inside and outside the respirator and analyzed by a calibrated optical particle counter over the particle-size range 0.

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Performance of dust respirators with facial seal leaks: II. Predictive model.

Am Ind Hyg Assoc J

October 1987

University of California Southern Occupational Health Center, UCLA School of Public Health 90024.

A performance model for half-mask and single-use respirators is presented. It represents a possible alternative to field measurements of respirator performance. Experimental data on filter and leak performance given in Part I were used to develop a model that allows one to predict 1) the overall respirator penetration as a function of particle size for any work rate and 2) overall total mass penetration for any work rate and exposure aerosol-size distribution for a known respirator filter and facial seal leak condition.

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