A comparative analysis of health surveillance strategies for administrative video display terminal employees.

Background: The objective of this study was to develop a strategy to optimize medical health surveillance protocols for administrative employees using video display terminals (VDTs). A total of 2453 medical examinations were analysed for VDT users in various sectors. From these data, using Bayesian statistics we inferred which factors were most relevant to medical diagnosis of the main disorders affecting VDT users.

A Bayesian assessment of occupational health surveillance in workers exposed to silica in the energy and construction industry.

Medical records generated during occupational health surveillance processes have large amounts of unexploited information that can help to reduce silica-related health risks and many occupational diseases. The methodology applied in this study consists in analyzing through machine learning techniques a database with 70,000 medical examinations from workers in the energy and construction industry in Spain. First, a general unsupervised Bayesian model is built and node force analysis is used to identify the factors with the greatest impact on the worker's health surveillance process.

Intercomparison exercise for gases emitted by a cement industry in Spain: a functional data approach.

This paper describes the results of an intercomparison exercise referring to the measurement of atmospheric pollutants emitted by cement plants. The research was conducted in 2008 in Catalonia, Spain. Thirteen Spanish companies accredited to make pollutant measurements and with suitably approved equipment and trained staff participated in the research.

Uncertainty determination methodology, sampling maps generation and trend studies with biomass thermogravimetric analysis.

This paper investigates a method for the determination of the maximum sampling error and confidence intervals of thermal properties obtained from thermogravimetric analysis (TG analysis) for several lignocellulosic materials (ground olive stone, almond shell, pine pellets and oak pellets), completing previous work of the same authors. A comparison has been made between results of TG analysis and prompt analysis. Levels of uncertainty and errors were obtained, demonstrating that properties evaluated by TG analysis were representative of the overall fuel composition, and no correlation between prompt and TG analysis exists.

Biomass thermogravimetric analysis: uncertainty determination methodology and sampling maps generation.

The objective of this study was to develop a methodology for the determination of the maximum sampling error and confidence intervals of thermal properties obtained from thermogravimetric analysis (TG), including moisture, volatile matter, fixed carbon and ash content. The sampling procedure of the TG analysis was of particular interest and was conducted with care. The results of the present study were compared to those of a prompt analysis, and a correlation between the mean values and maximum sampling errors of the methods were not observed.

Heterogenic solid biofuel sampling methodology and uncertainty associated with prompt analysis.

Accurate determination of the properties of biomass is of particular interest in studies on biomass combustion or cofiring. The aim of this paper is to develop a methodology for prompt analysis of heterogeneous solid fuels with an acceptable degree of accuracy. Special care must be taken with the sampling procedure to achieve an acceptable degree of error and low statistical uncertainty.