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Titlebook: Kafka’s Nonhuman Form; Troubling the Bounda Ted Geier Book 2016 The Editor(s) (if applicable) and The Author(s), under exclusive license to

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樓主: INFER
31#
發(fā)表于 2025-3-27 00:20:03 | 只看該作者
Cartesianism and the Spirit Controversyto predict the genetic subtype of glioblastoma using MRI (magnetic resonance imaging) volumes to make masks for accurate classification by dealing with the dataset assortment found in the medical domain datasets. The radiometric characteristics are analysed based on intensity, and the shape is mined
32#
發(fā)表于 2025-3-27 04:19:45 | 只看該作者
33#
發(fā)表于 2025-3-27 09:06:45 | 只看該作者
On Using Genetic Algorithm for Initialising Semi-supervised Fuzzy c-Means Clusteringster quality of the clustering algorithms. Results are compared with those produced by the existing ssFCM. While ssFCMGA and sGAs produced slightly lower agreement level than ssFCM with known class labels based on accuracy and NMI, the other six measurements showed improvement in the results in term
34#
發(fā)表于 2025-3-27 11:40:35 | 只看該作者
35#
發(fā)表于 2025-3-27 16:34:08 | 只看該作者
https://doi.org/10.1007/978-3-030-73551-7nach dem Modell der Paralleltest- bzw. der Retest-Zuverl?ssigkeit. Zu diesem Zweck wurden s?mtliche entwickelten Instrumente in einem Fragebogen zusammengefa?t und einer Gruppe von 90 Schülern zur Beantwortung vorgelegt. Der Fragebogen umfa?te im einzelnen:
36#
發(fā)表于 2025-3-27 18:12:59 | 只看該作者
Hans Bertram,Wolfgang Kreher,Irene Müller-Hartmannut the optimum clustering modality. After filtering and segmentation, SCG beats were clustered using the K-medoid algorithm. Clusters tended to correlate with the respiratory cycle, suggesting that breathing is a main source of SCG waveform variability. Identifying variability sources helps to accou
37#
發(fā)表于 2025-3-28 00:47:20 | 只看該作者
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