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Wyszukujesz frazę "Laass, M." wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
The origins of the cochlea and impedance matching hearing in synapsids
Autorzy:
Laaß, M.
Powiązania:
https://bibliotekanauki.pl/articles/20432.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Instytut Paleobiologii PAN
Tematy:
origin
cochlea
Therapsida
Anomodontia
tympanic hearing
Permian
South Africa
synapsid
tetrapod
Opis:
The origin of tympanic hearing in early synapsids is still controversial, because little is known about their inner ear and the function of their sound conducting apparatus. Here I describe the earliest known tympanic ear in the synapsid lineage, the ear of Pristerodon (Therapsida, Anomodontia) from the Late Permian of South Africa, which was virtually reconstructed from neutron tomographic data. Although Pristerodon is not a direct ancestor of mammals, its inner ear with distinctive cochlear cavity represents a connecting link between the primitive therapsid inner ear and the mammalian inner ear. The anatomy of the sound conducting apparatus of Pristerodon and the increased sound pressure transformer ratio points to a sensitivity to airborne sound. Furthermore, the origins of the cochlea and impedance matching hearing in synapsids coincided with the loss of contact between head and substrate, which already took place at least in Late Permian therapsids even before the postdentary bones became detached from the mandible.
Źródło:
Acta Palaeontologica Polonica; 2016, 61, 2
0567-7920
Pojawia się w:
Acta Palaeontologica Polonica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cognitive failure cluster enhancing the efficiency and the precision of the self-optimizing process model for bevel gear contact patterns
Autorzy:
Schmitt, R.
Niggemann, C.
Laass, M.
Powiązania:
https://bibliotekanauki.pl/articles/100025.pdf
Data publikacji:
2012
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
cognition
classification
self-optimization
gear testing
contact pattern
Opis:
The contact patterns of bevel gear sets are an important indicator for the acoustic quality of rear axle drives. The contact patterns are the result of complex interactions in the production process. This is due to many process steps, numerous influencing factors and interdependencies. In general, their effect on product variations is not fully comprehended. This impedes the design and control of the production process based on a holistic analytical model for new variants fulfilling the acoustic requirements. The approach with self-optimization is possible but can take a long time for the training of the artificial neural networks and the necessary iterations until a satisfying precision for the predicted process parameters is achieved. Also it can occur that the algorithm is not converging and therefore no satisfactory result is turned out at all. In this paper an approach is presented combining the flexibility of self-optimizing systems with the higher precision of delimited solution finders called the Cognitive Failure Cluster (CFC). The improvements provided by the clustering of the optimization program are evaluated regarding the training time and the precision of the result for a production lot of bevel gear sets.
Źródło:
Journal of Machine Engineering; 2012, 12, 1; 55-65
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cognition-based self-optimisation of an automotive rear-axle-drive production process
Autorzy:
Schmitt, R.
Niggemann, C.
Isermann, M.
Laass, M.
Matuschek, N.
Powiązania:
https://bibliotekanauki.pl/articles/99553.pdf
Data publikacji:
2010
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
Agent-Based Systems
cognition based
self-optimization
rear-axle-drive
Opis:
The production of automotive rear-axle drives is a complex process. This is due to many involved process steps, factors and interdependencies between processes, materials, means of production and individuals acting in this environment. In general their effect on product variations is not fully comprehended. Hence, a holistic analytical model is only possible in parts of the production. In this paper a modular approach is presented to make the production more flexible and enable it to react faster on product variations. This is achieved by a Cognitive Production System (CPS), which is based on accumulating, storing and processing of process knowledge so that it can be applied to similar cases. Through the combination and interaction of Cognitive Tolerance Matching (CTM) and Agent-based Systems the performance of the CPS is enhanced. The work discusses the set-up of such a CPS for the production of automotive rear-axle-drives with the focus on the failure state agent.
Źródło:
Journal of Machine Engineering; 2010, 10, 3; 68-77
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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