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Wyświetlanie 1-2 z 2
Tytuł:
Physiological strain in the Hungarian mining industry: The impact of physical and psychological factors
Autorzy:
Varga, József
Nagy, Imre
Szirtes, László
Pórszász, János
Powiązania:
https://bibliotekanauki.pl/articles/2177421.pdf
Data publikacji:
2016-06-30
Wydawca:
Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
Tematy:
work-related complex stress
physiological strain
health protection and promotion
work pulse
work-related accidents
workplace illumination
Opis:
Objectives The objectives of these investigations completed on workplaces in the Hungarian mining industry were to characterize the physiological strain of workers by means of work pulse and to examine the effects of work-related psychological factors. Material and Methods Continuous heart rate (HR) recording was completed on 71 miners over a total of 794 shifts between 1987 and 1992 in mining plants of the Hungarian mining industry using a 6-channel recorder – Bioport (ZAK, Germany). The work processes were simultaneously documented by video recording along with drawing up the traditional ergonomic workday schedule. All workers passed health evaluation for fitness for work. The effects of different psychological factors (simulated danger, “instrument stress,” presence of managers, and effect of prior involvement in accidents as well as different mining technologies and work place illumination) on the work pulse were evaluated. The statistical analysis was completed using SPSS software (version 13.0, SPSS Inc., USA). Results The work-related physiological strain differed between work places with different mining technologies in groups of 12–18 workers. The work pulse was lowest in bauxite mining (ΔHR = 22±8.9 bpm) and highest in drift drilling in dead rock with electric drilling machine (ΔHR = 30±6.9 bpm). During sham alarm situation the work pulse was significantly higher than during normal activities with the same physical task (ΔHR = 36.7±4.8 bpm vs. 25.8±1.6 bpm, p < 0.001). When work was performed under different psychological stress, the work pulse was consistently higher, while improving the work place illumination decreased the physiological strain appreciably (ΔHR (median, 25–75 percentiles) = 23, 20–26 bmp vs. 28, 25–31.3 bpm, p < 0.001). Conclusions Recording the heart rate during whole-shift work along with the work conditions gives reliable results and helps isolating factors that contribute to increased strain. The results can be used to implement preventive and health promotion measures.
Źródło:
International Journal of Occupational Medicine and Environmental Health; 2016, 29, 4; 597-611
1232-1087
1896-494X
Pojawia się w:
International Journal of Occupational Medicine and Environmental Health
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On wavelet based enhancing possibilities of fuzzy classification methods
Autorzy:
Lilik, Ferenc
Solecki, Levente
Sziová, Brigita
Kóczy, László T.
Nagy, Szilvia
Powiązania:
https://bibliotekanauki.pl/articles/384751.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
fuzzy classification
wavelet analysis
fuzzy rule interpolation
structural entropy
Opis:
If the antecedents of a fuzzy classification method are derived from pictures or measured data, it might have too many dimensions to handle. A classification scheme based on such data has to apply a careful selection or processing of the measured results: either a sampling, re‐ sampling is necessary. or the usage of functions, transfor‐ mations that reduce the long, high dimensional observed data vector or matrix into a single point or to a low num‐ ber of points. Wavelet analysis can be useful in such cases in two ways. As the number of resulting points of the wavelet ana‐ lysis is approximately half at each filters, a consecutive application of wavelet transform can compress the me‐ asurement data, thus reducing the dimensionality of the signal, i.e., the antecedent. An SHDSL telecommunication line evaluation is used to demonstrate this type of appli‐ cability, wavelets help in this case to overcome the pro‐ blem of a one dimensional signal sampling. In the case of using statistical functions, like mean, variance, gradient, edge density, Shannon or Rényi en‐ tropies for the extraction of the information from a pic‐ ture or a measured data set, and they don not produce enough information for performing the classification well enough, one or two consecutive steps of wavelet analy‐ sis and applying the same functions for the thus resulting data can extend the number of antecedents, and can dis‐ till such parameters that were invisible for these functi‐ ons in the original data set. We give two examples, two fuzzy classification schemes to show the improvement caused by wavelet analysis: a measured surface of a com‐ bustion engine cylinder and a colonoscopy picture. In the case of the first example the wear degree is to be deter‐ mine, in the case of the second one, the roundish polyp content of the picture. In the first case the applied statisti‐ cal functions are Rényi entropy differences, the structural entropies, in the second case mean, standard deviation, Canny filtered edge density, gradients and the entropies. In all the examples stabilized KH rule interpolation was used to treat sparse rulebases.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 2; 32-41
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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