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Titlebook: Lessing-Handbuch; Leben – Werk – Wirku Monika Fick Book 2016Latest edition Springer-Verlag Berlin Heidelberg 2016 Gotthold Ephraim Lessing.

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发表于 2025-3-21 17:15:25 | 显示全部楼层 |阅读模式
书目名称Lessing-Handbuch
副标题Leben – Werk – Wirku
编辑Monika Fick
视频video
概述Mit einem neuen Kapitel: Lessing und die jüdischen Aufklärung.Wichtiger Autor in Schule, Studium und an deutschsprachigen Bühnen.Inklusive Zeittafel, Bibliografie, Werk-, Sach- und Namenregister
图书封面Titlebook: Lessing-Handbuch; Leben – Werk – Wirku Monika Fick Book 2016Latest edition Springer-Verlag Berlin Heidelberg 2016 Gotthold Ephraim Lessing.
描述Die um ein großes Kapitel zur jüdischen Aufklärung erweiterte und aktualisierte vierte Auflage des Standardwerks vermittelt einen Zugang zum Gesamtwerk Gotthold Ephraim Lessings und ergänzt mit einer Fülle von Interpretationen das aktuelle Lessingbild. Das Handbuch bietet zu jedem Werk und zu jeder Werkgruppe neue Forschungsreferate und Analysen auf aktuellem Stand.
出版日期Book 2016Latest edition
关键词Gotthold Ephraim Lessing; Christoph Martin Wieland; Deutsche Literatur; Friedrich Schlegel; Lessing-Hand
版次4
doihttps://doi.org/10.1007/978-3-476-05399-2
isbn_softcover978-3-476-02577-7
isbn_ebook978-3-476-05399-2
copyrightSpringer-Verlag Berlin Heidelberg 2016
The information of publication is updating

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发表于 2025-3-21 20:17:23 | 显示全部楼层
oduced to make up for this shortcoming. In this paper, we introduce a DL-based KT model referred to as Convolutional Attention Knowledge Tracing (CAKT) utilizing attention mechanism to augment Convolutional Neural Network (CNN) in order to enhance the ability of modeling longer range dependencies.
发表于 2025-3-22 04:09:13 | 显示全部楼层
Monika FickIn this paper, we presented a sentence preprocessing method that extracts the leftmost longest common sequence to obtain the common and difference subsequences between the rumor text and its explanation text to compose samples and train a supervised model for classification between rumors and explan
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Monika Fickal results conducted in this paper compare the accuracy, efficiency, and stability of various algorithms using synthetic datasets, Sushi datasets, and Irish datasets, which demonstrate the effectiveness of our proposed algorithm in real-world scenarios.
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Monika Fickent. Additionally, it proposes an improved Temporal Convolutional Network (TCN) named Temporal Convolutional Sparse Multilayer Perceptron Network (TCSMN). This network captures sequential structural features of cells and their surrounding neighbors, enhancing the ability to extract semantic features
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发表于 2025-3-23 05:41:48 | 显示全部楼层
Monika Fickwith tournament selection. Furthermore, power-law selection outperforms UMDA and the (1+1) EA in our experiments on the .-. and . k-. problems, but yields to the .-selection, tournament selection, and the self-adaptive MOSA-EA. On the unicost set cover problems, the EA with power-law selection shows
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