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Titlebook: Zircon, Zirconium, Zirconia - Similar Names, Different Materials; Bo?ena Arnold Book 2022 Springer-Verlag GmbH Germany, part of Springer N

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樓主: Opiate
21#
發(fā)表于 2025-3-25 07:02:25 | 只看該作者
Ulrike Knaueren alle Zwangskr?fte eliminiert werden, dann verschwinden die Lagrange‐Multiplikatoren . und, da die Bindungsgleichung . entf?llt, vereinfacht sich (5.1 ) zu einem System gew?hnlicher Differentialgleichungen. Die im Lagevektor . zusammengefassten verallgemeinerten Koordinaten beschreiben in eindeuti
22#
發(fā)表于 2025-3-25 10:05:08 | 只看該作者
Characterisation of Viscoelastic Material Properties During Curing Processes,e viscoelastic solid behaviour is performed using a dynamic mechanical analyser. The aim of this work is to investigate the dependence of the viscoelastic response on time, temperature and degree of cure and to derive a model that covers the dependency of the relaxation modulus on all three factors
23#
發(fā)表于 2025-3-25 15:06:12 | 只看該作者
24#
發(fā)表于 2025-3-25 17:29:27 | 只看該作者
25#
發(fā)表于 2025-3-25 22:04:22 | 只看該作者
Effect of Fines Content on Dynamic Properties of Sand Using Bender Element,eotechnical engineering. Shear wave velocity (V.) and small-strain shear modulus (G.) are the key parameters in defining material response to various dynamic loadings. Generally, sand is weak in dynamic loading and also contains few non-plastic fines up to a certain extent. Thus, to have a better fu
26#
發(fā)表于 2025-3-26 01:22:15 | 只看該作者
27#
發(fā)表于 2025-3-26 05:49:31 | 只看該作者
28#
發(fā)表于 2025-3-26 12:33:45 | 只看該作者
29#
發(fā)表于 2025-3-26 15:21:59 | 只看該作者
Image-Based Object Spoofing Detectionpproach is able to distinguish with high accuracy a real photo from an attack. Regarding the public database, the results were obtained with existing methods, as the best HTER results using a single frame approach.
30#
發(fā)表于 2025-3-26 17:41:28 | 只看該作者
Kerstin Bauer,Jürgen Ennker,Stefan Bauererformance in the validation set would be selected. To our knowledge, it is the first systematic study to examine a weight-selection strategy on training DNN for imbalanced classification. Demonstrated by experiments on 10 imbalanced datasets obtained from MNIST, the DNN trained by our new strategy
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