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Abstract

The considerations presented in this paper include a computer analysis of slide bearing wear prognosis using the solutions of recurrence equations complemented with the experimental data values. On the ground of the results obtained from analytical and computational numerical calculations, and taking into account the experimental parameters of bearing material and operation boundary conditions, the control problems of slide bearing wear surfaces have been presented. The obtained results allow us to see a connection between roughness, material properties, the amplitude of vibrations, the kind of the friction forces, the hardness of materials, the sliding speed in one side and the wear increments in succeeding time units of the exploitation process in other side.

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Authors and Affiliations

Andrzej Miszczak
Krzysztof Wierzcholski
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Abstract

This paper presents a new form of a mathematical estimation of stochastic bio-hydrodynamic lubrication parameters for real human joint surfaces with phospholipid bilayers. In this work, the authors present the analytical and stochastic considerations, which are based on the measurements of human joint surfaces. The gap is restricted between two cooperating biological surfaces. After numerous experimental measurements, it directly follows that the random symmetrical as well as unsymmetrical increments and decrements of the gap height in human joints influence the hydrodynamic pressure, load-carrying capacity, friction forces, and wear of the cooperating cartilage surfaces in human joints. The main focus of the paper was to demonstrate the influence of variations in the expected values and standard deviation of human joint gap height on the hydrodynamic lubrication parameters occurring in the human joint. It is very important to notice that the new form of apparent dynamic viscosity of synovial fluid formulated by the authors depends on ultra-thin gap height variations. Moreover, evident connection was observed between the apparent dynamic viscosity and the properties of cartilage surface coated by phospholipid cells. The above observations indicate an indirect impact of stochastic changes in the height of the gap and the indirect impact of random changes in the properties of the joint surface coated with the phospholipid layers, on the value of hydrodynamic pressure, load carrying capacity and friction forces. In this paper the authors present a synthetic, comprehensive estimation of stochastic bio-hydrodynamic lubrication parameters for the cooperating, rotational cartilage bio-surfaces with phospholipid bilayers occurring in human joints. The new results presented in this paper were obtained taking into account 3D variations in the dynamic viscosity of synovial fluid, particularly random variations crosswise the film thickness for non-Newtonian synovial fluid properties. According to the authors’ knowledge, the obtained results are widely applicable in spatiotemporal models in biology and health science.
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Bibliography

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Authors and Affiliations

Krzysztof Wierzcholski
1
ORCID: ORCID
Andrzej Miszczak
2
ORCID: ORCID

  1. WSG University of Economy in Bydgoszcz, ul. Garbary 2, 85-229 Bydgoszcz, Poland
  2. Gdynia Maritime University, ul. Morska 81/87, 81-225 Gdynia, Poland
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Abstract

In recent years, a lot of attention has been paid to deep learning methods in the context of vision-based construction site safety systems. However, there is still more to be done to establish the relationship between supervised construction workers and their essential personal protective equipment, like hard hats. A deep learning method combining object detection, head center localization, and simple rule-based reasoning is proposed in this article. In tests, this solution surpassed the previous methods based on the relative bounding box position of different instances and direct detection of hard hat wearers and non-wearers. Achieving MS COCO style overall AP of 67.5% compared to 66.4% and 66.3% achieved by the approaches mentioned above, with class-specific AP for hard hat non-wearers of 64.1% compared to 63.0% and 60.3%. The results show that using deep learning methods with a humanly interpretable rule-based algorithm is better suited for detecting hard hat non-wearers.
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Authors and Affiliations

Bartosz Wójcik
1
ORCID: ORCID
Mateusz Żarski
1
ORCID: ORCID
Kamil Książek
1
Jarosław A. Miszczak
1
Mirosław J. Skibniewski
1 2

  1. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, 44-100 Gliwice, Poland
  2. A. James Clark School of Engineering, University of Maryland, College Park, MD 20742-3021, USA
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Abstract

The article analyses the changes occurring in accidents in the construction industry in Poland. It was analyzed the influence of the season on the number and structure of accidents. Research and analyzes were carried out on the basis of statistical data, made available by the Central Statistical Office, regarding accidents at work in construction that occurred in the period from 2010 to 2018. The total number of accidents at work in the construction sector in in these years shows a significant downward trend. A similar downward trend can also be seen in individual groups of accidents, broken down into light, serious and fatal. Based on the research carried out, the decisive impact of the season on the accident rates in construction sector was noticed. The smallest value of the accident frequency rate in most of the accident types considered can be observed in the winter season. In turn, the highest value of the light and fatal accident frequency rate can be observed in summer season (July - September). Weather conditions, for example, high temperatures and sunshine can lead to dangerous situations which can result in accidents at work. Climate conditions should therefore play an increasingly important role in assessing the risk of accidents.
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Authors and Affiliations

Iwona Szer
1
ORCID: ORCID
Jacek Szer
1
ORCID: ORCID
Monika Kaszubska
1
ORCID: ORCID
Jakub Miszczak
1
ORCID: ORCID
Bożena Hoła
2
ORCID: ORCID
Ewa Błazik-Borowa
3
ORCID: ORCID
Marek Jabłoński
1
ORCID: ORCID

  1. Lodz University of Technology, Department of Building Materials Physics and Sustainable Design, Politechniki 6, 90-924 Łódź, Poland
  2. Wroclaw University of Science and Technology, Faculty of Civil Engineering, pl. Grunwaldzki 11, 50-377 Wrocław, Poland
  3. Lublin University of Technology, Faculty of Civil Engineering and Architecture, ul. Nadbystrzycka 40, 20-618 Lublin, Poland

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