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Titlebook: Einführung Inventor 2019; Von der 2D-Skizze zu Uwe Grellmann Textbook 2020 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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發(fā)表于 2025-3-26 22:31:41 | 只看該作者
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發(fā)表于 2025-3-27 03:52:11 | 只看該作者
The Technical Committee on Fault Tolerant Computing of The IEEE Computer Society,he IEEE Computer Group (IEEE-CG) that a Technical Committee on Fault-Tolerant Computing (TC-FTC) should be formed to promote further activities in this field. The approval of the IEEE-CG Administrative Committee was granted on November 18, 1969. A letter from Computer Group Chairman E. J. McCluskey,
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發(fā)表于 2025-3-27 06:30:12 | 只看該作者
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發(fā)表于 2025-3-27 12:38:38 | 只看該作者
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發(fā)表于 2025-3-27 17:37:14 | 只看該作者
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發(fā)表于 2025-3-27 20:45:53 | 只看該作者
Fungi as Parasites: A Conspectus of the Fossil Record,ction, parasitism is perhaps the most difficult to demonstrate in the fossil record. Different lines of evidence obtained from both the host and fungus are required to safely discriminate parasitic fungi from saprotrophs and even mutualists when examined in fossils.
37#
發(fā)表于 2025-3-28 00:58:25 | 只看該作者
Elmar Holensteineos. We use the TensorFlow library and two pre-trained models: . and ., with an official (academic) pornography dataset including associated labelling. The performance of each model was investigated. The final solution was delivered as an iOS application to detect and classify photos and live videos
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發(fā)表于 2025-3-28 02:05:10 | 只看該作者
39#
發(fā)表于 2025-3-28 08:35:34 | 只看該作者
Ahmed Abdul Haleem Khanhe food system...?..The atlas results from an exhaustive survey and research work conducted in Lisbon Metropolitan Area for a research project, SPLACH – Spatial Planning for Change, for the past 3 years, in terms of the analysis of its Food System and Urban Planning, aiming to inform the delineation of planning 978-3-030-94835-1978-3-030-94833-7
40#
發(fā)表于 2025-3-28 10:40:48 | 只看該作者
MaxSMT-Based Type Inference for Python 3 constraints and specific quantifier instantiation patterns to make the constraint solving process efficient. Our experimental evaluation shows that . scales to real world Python programs and outperforms state-of-the-art tools.
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