One of the authors of the study, Teresa Rivas, from the Mining Engineering School at this university explained to SINC that job duration is also related to adopting bad positions and lack of knowledge of regulations, as a result of which shorter tasks are associated with more falls and less well-trained workers. On the other hand, workers that carry out longer tasks are better prepared for dangerous situations.
To carry out this study, authors surveyed almost 400 workers from 103 companies from industry, construction and the services sector while performing their tasks at height. Bayesian networks, one of the so called “automatic learning” statistical techniques enabling graphic expression of relations of dependence between variables, as well as making estimates in probalistic terms of the influence of each variable and its interaction in the type of fall, were used to analyse researchers’ data.
In previous work these scientists have already analysed the capacity of predicting and interpreting different automatic learning techniques and concluded that Bayesian networks, apart from having a comparable predictive capacity to other statistical methods, “have an excellent interpretative capacity”. Rivas points out that Bayesian networks can be improved with new data, as a result of which they are a very useful tool for identifying causes of accidents and establishing the bases of understanding for a “solidly based” prevention policy.
José María Matías, mathematician from the Department of Statistics at the University of Vigo who also participated in the study, says that these types of techniques can be used for analysing causes “because there is continuous data on victims of work accidents, but beyond just the numbers what we need to look for is how to avoid such accidents, and this is where these methodological contributions play an important role”.
The researcher Rivas concluded that knowing the dependence relationship between the causes of the accident offers experts useful information for improving health and safety at work management models.Referencias bibliográficas:
J. M. Matías, T. Rivas, J. E. Martín, J. Taboada. A machine learning methodology for the analysis of workplace accidents. International Journal of Computer Mathematics (85):3-4, 559 – 578 Marzo-Abril 2008
SINC Team | alfa
Physics of bubbles could explain language patterns
25.07.2017 | University of Portsmouth
Obstructing the ‘inner eye’
07.07.2017 | Friedrich-Schiller-Universität Jena
Strong light-matter coupling in these semiconducting tubes may hold the key to electrically pumped lasers
Light-matter quasi-particles can be generated electrically in semiconducting carbon nanotubes. Material scientists and physicists from Heidelberg University...
Fraunhofer IPA has developed a proximity sensor made from silicone and carbon nanotubes (CNT) which detects objects and determines their position. The materials and printing process used mean that the sensor is extremely flexible, economical and can be used for large surfaces. Industry and research partners can use and further develop this innovation straight away.
At first glance, the proximity sensor appears to be nothing special: a thin, elastic layer of silicone onto which black square surfaces are printed, but these...
3-D shape acquisition using water displacement as the shape sensor for the reconstruction of complex objects
A global team of computer scientists and engineers have developed an innovative technique that more completely reconstructs challenging 3D objects. An ancient...
Physicists have developed a new technique that uses electrical voltages to control the electron spin on a chip. The newly-developed method provides protection from spin decay, meaning that the contained information can be maintained and transmitted over comparatively large distances, as has been demonstrated by a team from the University of Basel’s Department of Physics and the Swiss Nanoscience Institute. The results have been published in Physical Review X.
For several years, researchers have been trying to use the spin of an electron to store and transmit information. The spin of each electron is always coupled...
What is the mass of a proton? Scientists from Germany and Japan successfully did an important step towards the most exact knowledge of this fundamental constant. By means of precision measurements on a single proton, they could improve the precision by a factor of three and also correct the existing value.
To determine the mass of a single proton still more accurate – a group of physicists led by Klaus Blaum and Sven Sturm of the Max Planck Institute for Nuclear...
21.07.2017 | Event News
19.07.2017 | Event News
12.07.2017 | Event News
25.07.2017 | Physics and Astronomy
25.07.2017 | Earth Sciences
25.07.2017 | Life Sciences