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Titlebook: Computational Science – ICCS 2021; 21st International C Maciej Paszynski,Dieter Kranzlmüller,Peter M.A. Sl Conference proceedings 2021 Spri

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發(fā)表于 2025-3-23 12:42:00 | 只看該作者
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Improved Design Closure of Compact Microwave Circuits by Means of Performance Requirement Adaptationlied at the later stages of the design process to tune the geometry and/or material parameter values. To ensure sufficient accuracy, parameter adjustment is realized at the level of full-wave electromagnetic (EM) analysis, which creates perhaps the most important bottleneck due to the entailed compu
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發(fā)表于 2025-3-24 08:55:36 | 只看該作者
Graph-Grammar Based Longest-Edge Refinement Algorithm for Three-Dimensional Optimally , Refined Meshtion layers are often constructed from tetrahedral finite elements. The refinement algorithms that avoids hanging nodes are desired in order to avoid constrained approximation on broken edges and faces. We present a new mesh refinement algorithm for such the tetrahedral grids, with the following fea
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發(fā)表于 2025-3-24 10:42:07 | 只看該作者
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發(fā)表于 2025-3-24 16:54:52 | 只看該作者
Lecture Notes in Computer Sciencenment, and sports. This paper presents how ML can be used for detecting fake news. The problem of online disinformation has recently become one of the most challenging issues of computer science. Methods: in this research, a fake news detection method based on multi classifiers (CNN, XGBoost, Random
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發(fā)表于 2025-3-24 22:12:20 | 只看該作者
Informational Boundary Work in Everyday Lifel metrics were proposed as a measure of the model quality assessment. Neural network architectures, based on the state-of-the-art solutions of the Transformer type were applied to create the models. The computing capabilities of the Google Colaboratory remote platform, as well as the Flair library,
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發(fā)表于 2025-3-24 23:16:24 | 只看該作者
Sustainable Digital Communitiesanation methods is to provide an insight into the decision process of AI system, their underlying mechanisms may differ. This may result in very different explanations for the same tasks. In this work, we present an approach that aims at combining several XAI algorithms into one ensemble explanation
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